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<h1 style="">Natural Language Processing Nanodegree</h1>
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<p><strong>Nanodegree key:</strong> nd892</p>
<p><strong>Version:</strong> 1.0.0</p>
<p><strong>Locale:</strong> en-us</p>
<p><p>Master the skills to get computers to understand, process, and manipulate human language. Build models on real data, and get hands-on experience with sentiment analysis, machine translation, and more.</p></p>
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<h3>Content</h3>
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<h4><strong>Part 01 <em>(FreePreview)</em>:</strong> Welcome to Natural Language Processing</h4>
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<strong>Module 01:</strong> Welcome to Natural Language Processing
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<a "Part 01-Module 01-Lesson 01_Welcome to Natural Language Processing/index.html"><strong>Lesson 01:</strong> Welcome to Natural Language Processing</a>
<p><p>Welcome to a Free Preview of the Natural Language Processing Nanodegree program! Come and take a sneak peek at what our program offers.</p></p>
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<a "Part 01-Module 01-Lesson 01_Welcome to Natural Language Processing/01. Program Syllabus.html"><strong>Concept 01:</strong> Program Syllabus</a>
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<a "Part 01-Module 01-Lesson 01_Welcome to Natural Language Processing/02. School of AI Team.html"><strong>Concept 02:</strong> School of AI Team</a>
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<a "Part 01-Module 01-Lesson 01_Welcome to Natural Language Processing/03. NLP Overview.html"><strong>Concept 03:</strong> NLP Overview</a>
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<a "Part 01-Module 01-Lesson 01_Welcome to Natural Language Processing/04. Context Is Everything.html"><strong>Concept 04:</strong> Context Is Everything</a>
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<a "Part 01-Module 01-Lesson 01_Welcome to Natural Language Processing/05. NLP and IBM Watson.html"><strong>Concept 05:</strong> NLP and IBM Watson</a>
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<a "Part 01-Module 01-Lesson 01_Welcome to Natural Language Processing/06. Towards Augmented Intelligence.html"><strong>Concept 06:</strong> Towards Augmented Intelligence</a>
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<h4><strong>Part 02 <em>(FreePreview)</em>:</strong> Building an NLP Pipeline</h4>
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<strong>Module 01:</strong> Building an NLP Pipeline
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<a "Part 02-Module 01-Lesson 01_Building an NLP Pipeline/index.html"><strong>Lesson 01:</strong> Building an NLP Pipeline</a>
<p><p>Learn about text processing, feature extraction, and part-of-speech tagging.</p></p>
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<a "Part 02-Module 01-Lesson 01_Building an NLP Pipeline/01. NLP and Pipelines.html"><strong>Concept 01:</strong> NLP and Pipelines</a>
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<a "Part 02-Module 01-Lesson 01_Building an NLP Pipeline/02. How NLP Pipelines Work.html"><strong>Concept 02:</strong> How NLP Pipelines Work</a>
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<a "Part 02-Module 01-Lesson 01_Building an NLP Pipeline/03. Text Processing.html"><strong>Concept 03:</strong> Text Processing</a>
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<a "Part 02-Module 01-Lesson 01_Building an NLP Pipeline/04. Counting Words.html"><strong>Concept 04:</strong> Counting Words</a>
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<a "Part 02-Module 01-Lesson 01_Building an NLP Pipeline/05. Feature Extraction.html"><strong>Concept 05:</strong> Feature Extraction</a>
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<a "Part 02-Module 01-Lesson 01_Building an NLP Pipeline/06. Modeling.html"><strong>Concept 06:</strong> Modeling</a>
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<a "Part 02-Module 01-Lesson 01_Building an NLP Pipeline/07. Quiz Split Sentences.html"><strong>Concept 07:</strong> Quiz: Split Sentences</a>
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<a "Part 02-Module 01-Lesson 01_Building an NLP Pipeline/08. Part-of-Speech Tagging.html"><strong>Concept 08:</strong> Part-of-Speech Tagging</a>
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<a "Part 02-Module 01-Lesson 01_Building an NLP Pipeline/09. Named Entity Recognition.html"><strong>Concept 09:</strong> Named Entity Recognition</a>
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<a "Part 02-Module 01-Lesson 01_Building an NLP Pipeline/10. Bag of Words.html"><strong>Concept 10:</strong> Bag of Words</a>
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<a "Part 02-Module 01-Lesson 01_Building an NLP Pipeline/11. TF-IDF.html"><strong>Concept 11:</strong> TF-IDF</a>
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<a "Part 02-Module 01-Lesson 01_Building an NLP Pipeline/12. One-Hot Encoding.html"><strong>Concept 12:</strong> One-Hot Encoding</a>
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<a "Part 02-Module 01-Lesson 01_Building an NLP Pipeline/13. Word Embeddings.html"><strong>Concept 13:</strong> Word Embeddings</a>
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<a "Part 02-Module 01-Lesson 01_Building an NLP Pipeline/14. t-SNE.html"><strong>Concept 14:</strong> t-SNE</a>
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<h4><strong>Part 03 <em>(FreePreview)</em>:</strong> Voice User Interfaces</h4>
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<strong>Module 01:</strong> Voice User Interfaces
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<a "Part 03-Module 01-Lesson 01_Voice User Interfaces/index.html"><strong>Lesson 01:</strong> Voice User Interfaces</a>
<p><p>Learn about phonetics, acoustic models, and deep neural networks.</p></p>
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<a "Part 03-Module 01-Lesson 01_Voice User Interfaces/01. Welcome to Voice User Interfaces!.html"><strong>Concept 01:</strong> Welcome to Voice User Interfaces!</a>
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<a "Part 03-Module 01-Lesson 01_Voice User Interfaces/02. VUI Overview.html"><strong>Concept 02:</strong> VUI Overview</a>
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<a "Part 03-Module 01-Lesson 01_Voice User Interfaces/03. VUI Applications.html"><strong>Concept 03:</strong> VUI Applications</a>
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<a "Part 03-Module 01-Lesson 01_Voice User Interfaces/04. Conversational AI with Alexa.html"><strong>Concept 04:</strong> Conversational AI with Alexa</a>
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<a "Part 03-Module 01-Lesson 01_Voice User Interfaces/05. Lab Space Geek.html"><strong>Concept 05:</strong> Lab: Space Geek</a>
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<a "Part 03-Module 01-Lesson 01_Voice User Interfaces/06. Challenges in ASR.html"><strong>Concept 06:</strong> Challenges in ASR</a>
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<a "Part 03-Module 01-Lesson 01_Voice User Interfaces/07. Phonetics.html"><strong>Concept 07:</strong> Phonetics</a>
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<a "Part 03-Module 01-Lesson 01_Voice User Interfaces/08. Quiz Phonetics.html"><strong>Concept 08:</strong> Quiz: Phonetics</a>
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<a "Part 03-Module 01-Lesson 01_Voice User Interfaces/09. Acoustic Models and the Trouble with Time.html"><strong>Concept 09:</strong> Acoustic Models and the Trouble with Time</a>
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<a "Part 03-Module 01-Lesson 01_Voice User Interfaces/10. Language Models.html"><strong>Concept 10:</strong> Language Models</a>
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<a "Part 03-Module 01-Lesson 01_Voice User Interfaces/11. Deep Neural Networks as Speech Models.html"><strong>Concept 11:</strong> Deep Neural Networks as Speech Models</a>
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<h4><strong>Part 04 <em>(FreePreview)</em>:</strong> What's Next?</h4>
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<strong>Module 01:</strong> What's Next?
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<a "Part 04-Module 01-Lesson 01_What's Next/index.html"><strong>Lesson 01:</strong> What's Next?</a>
<p><p>Here's how to keep building your NLP expertise!</p></p>
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<a "Part 04-Module 01-Lesson 01_What's Next/01. Ready to Level Up with NLP.html"><strong>Concept 01:</strong> Ready to Level Up with NLP?</a>
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<h4><strong>Part 05 :</strong> Introduction to Natural Language Processing</h4>
<p><p>This section provides an overview of the program and introduces the fundamentals of Natural Language Processing through symbolic manipulation, including text cleaning, normalization, and tokenization. You'll then build a part of speech tagger using hidden Markov models.</p></p>
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<strong>Module 01:</strong> Introduction to the Nanodegree
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<a "Part 05-Module 01-Lesson 01_Welcome to Natural Language Processing/index.html"><strong>Lesson 01:</strong> Welcome to Natural Language Processing</a>
<p><p>Welcome to the Natural Language Processing Nanodegree program!</p></p>
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<a "Part 05-Module 01-Lesson 01_Welcome to Natural Language Processing/01. Welcome to the Natural Language Processing Nanodegree.html"><strong>Concept 01:</strong> Welcome to the Natural Language Processing Nanodegree</a>
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<a "Part 05-Module 01-Lesson 01_Welcome to Natural Language Processing/02. Deadline Policy.html"><strong>Concept 02:</strong> Deadline Policy</a>
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<a "Part 05-Module 01-Lesson 01_Welcome to Natural Language Processing/03. Community Guidelines.html"><strong>Concept 03:</strong> Community Guidelines</a>
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<a "Part 05-Module 01-Lesson 01_Welcome to Natural Language Processing/04. Lesson Plan - Week 1.html"><strong>Concept 04:</strong> Lesson Plan - Week 1</a>
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<a "Part 05-Module 01-Lesson 02_Udacity Support/index.html"><strong>Lesson 02:</strong> Udacity Support</a>
<p><p>Learn about the support you'll have access to during your Nanodegree program!</p></p>
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<a "Part 05-Module 01-Lesson 02_Udacity Support/01. Udacity Support.html"><strong>Concept 01:</strong> Udacity Support</a>
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<a "Part 05-Module 01-Lesson 03_Intro to NLP/index.html"><strong>Lesson 03:</strong> Intro to NLP</a>
<p><p>Arpan will give you an overview of how to build a Natural Language Processing pipeline.</p></p>
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<a "Part 05-Module 01-Lesson 03_Intro to NLP/01. Introducing Arpan.html"><strong>Concept 01:</strong> Introducing Arpan</a>
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<a "Part 05-Module 01-Lesson 03_Intro to NLP/02. NLP Overview.html"><strong>Concept 02:</strong> NLP Overview</a>
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<a "Part 05-Module 01-Lesson 03_Intro to NLP/03. Structured Languages.html"><strong>Concept 03:</strong> Structured Languages</a>
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<a "Part 05-Module 01-Lesson 03_Intro to NLP/04. Grammar.html"><strong>Concept 04:</strong> Grammar</a>
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<a "Part 05-Module 01-Lesson 03_Intro to NLP/05. Unstructured Text.html"><strong>Concept 05:</strong> Unstructured Text</a>
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<a "Part 05-Module 01-Lesson 03_Intro to NLP/06. Counting Words.html"><strong>Concept 06:</strong> Counting Words</a>
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<a "Part 05-Module 01-Lesson 03_Intro to NLP/07. Context Is Everything.html"><strong>Concept 07:</strong> Context Is Everything</a>
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<a "Part 05-Module 01-Lesson 03_Intro to NLP/08. NLP and Pipelines.html"><strong>Concept 08:</strong> NLP and Pipelines</a>
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<a "Part 05-Module 01-Lesson 03_Intro to NLP/09. How NLP Pipelines Work.html"><strong>Concept 09:</strong> How NLP Pipelines Work</a>
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<a "Part 05-Module 01-Lesson 03_Intro to NLP/10. Text Processing.html"><strong>Concept 10:</strong> Text Processing</a>
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<a "Part 05-Module 01-Lesson 03_Intro to NLP/11. Feature Extraction.html"><strong>Concept 11:</strong> Feature Extraction</a>
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<a "Part 05-Module 01-Lesson 03_Intro to NLP/12. Modeling.html"><strong>Concept 12:</strong> Modeling</a>
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<a "Part 05-Module 01-Lesson 04_Text Processing/index.html"><strong>Lesson 04:</strong> Text Processing</a>
<p><p>Learn to prepare text obtained from different sources for further processing, by cleaning, normalizing and splitting it into individual words or tokens.</p></p>
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<a "Part 05-Module 01-Lesson 04_Text Processing/01. Text Processing.html"><strong>Concept 01:</strong> Text Processing</a>
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<a "Part 05-Module 01-Lesson 04_Text Processing/02. Coding Exercises.html"><strong>Concept 02:</strong> Coding Exercises</a>
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<a "Part 05-Module 01-Lesson 04_Text Processing/03. Introduction to GPU Workspaces.html"><strong>Concept 03:</strong> Introduction to GPU Workspaces</a>
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<a "Part 05-Module 01-Lesson 04_Text Processing/04. Workspaces Best Practices.html"><strong>Concept 04:</strong> Workspaces: Best Practices</a>
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<a "Part 05-Module 01-Lesson 04_Text Processing/05. Workspace.html"><strong>Concept 05:</strong> Workspace</a>
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<a "Part 05-Module 01-Lesson 04_Text Processing/06. Capturing Text Data.html"><strong>Concept 06:</strong> Capturing Text Data</a>
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<a "Part 05-Module 01-Lesson 04_Text Processing/07. Cleaning.html"><strong>Concept 07:</strong> Cleaning</a>
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<a "Part 05-Module 01-Lesson 04_Text Processing/08. Normalization.html"><strong>Concept 08:</strong> Normalization</a>
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<a "Part 05-Module 01-Lesson 04_Text Processing/09. Tokenization.html"><strong>Concept 09:</strong> Tokenization</a>
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<a "Part 05-Module 01-Lesson 04_Text Processing/10. Stop Word Removal.html"><strong>Concept 10:</strong> Stop Word Removal</a>
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<a "Part 05-Module 01-Lesson 04_Text Processing/11. Part-of-Speech Tagging.html"><strong>Concept 11:</strong> Part-of-Speech Tagging</a>
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<a "Part 05-Module 01-Lesson 04_Text Processing/12. Named Entity Recognition.html"><strong>Concept 12:</strong> Named Entity Recognition</a>
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<a "Part 05-Module 01-Lesson 04_Text Processing/13. Stemming and Lemmatization.html"><strong>Concept 13:</strong> Stemming and Lemmatization</a>
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<a "Part 05-Module 01-Lesson 04_Text Processing/14. Summary.html"><strong>Concept 14:</strong> Summary</a>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/index.html"><strong>Lesson 05:</strong> Spam Classifier with Naive Bayes</a>
<p><p>In this section, you'll learn how to build a spam e-mail classifier using the naive Bayes algorithm.</p></p>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/01. Intro.html"><strong>Concept 01:</strong> Intro</a>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/02. Guess the Person.html"><strong>Concept 02:</strong> Guess the Person</a>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/03. Known and Inferred.html"><strong>Concept 03:</strong> Known and Inferred</a>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/04. Guess the Person Now.html"><strong>Concept 04:</strong> Guess the Person Now</a>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/05. Bayes Theorem.html"><strong>Concept 05:</strong> Bayes Theorem</a>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/06. Quiz False Positives.html"><strong>Concept 06:</strong> Quiz: False Positives</a>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/07. Solution False Positives.html"><strong>Concept 07:</strong> Solution: False Positives</a>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/08. Bayesian Learning 1.html"><strong>Concept 08:</strong> Bayesian Learning 1</a>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/09. Bayesian Learning 2.html"><strong>Concept 09:</strong> Bayesian Learning 2</a>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/10. Bayesian Learning 3.html"><strong>Concept 10:</strong> Bayesian Learning 3</a>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/11. Naive Bayes Algorithm 1.html"><strong>Concept 11:</strong> Naive Bayes Algorithm 1</a>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/12. Naive Bayes Algorithm 2.html"><strong>Concept 12:</strong> Naive Bayes Algorithm 2</a>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/13. Building a Spam Classifier.html"><strong>Concept 13:</strong> Building a Spam Classifier</a>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/14. Project.html"><strong>Concept 14:</strong> Project</a>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/15. Spam Classifier - Workspace.html"><strong>Concept 15:</strong> Spam Classifier - Workspace</a>
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<a "Part 05-Module 01-Lesson 05_Spam Classifier with Naive Bayes/16. Outro.html"><strong>Concept 16:</strong> Outro</a>
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<a "Part 05-Module 01-Lesson 06_Part of Speech Tagging with HMMs/index.html"><strong>Lesson 06:</strong> Part of Speech Tagging with HMMs</a>
<p><p>Luis will give you an overview of several part-of-speech tagging, including a deeper dive on hidden Markov models.</p></p>
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<a "Part 05-Module 01-Lesson 06_Part of Speech Tagging with HMMs/01. Intro.html"><strong>Concept 01:</strong> Intro</a>
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<a "Part 05-Module 01-Lesson 06_Part of Speech Tagging with HMMs/02. Part of Speech Tagging.html"><strong>Concept 02:</strong> Part of Speech Tagging</a>
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<a "Part 05-Module 01-Lesson 06_Part of Speech Tagging with HMMs/03. Lookup Table.html"><strong>Concept 03:</strong> Lookup Table</a>
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<a "Part 05-Module 01-Lesson 06_Part of Speech Tagging with HMMs/04. Bigrams.html"><strong>Concept 04:</strong> Bigrams</a>
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<a "Part 05-Module 01-Lesson 06_Part of Speech Tagging with HMMs/05. When bigrams won't work.html"><strong>Concept 05:</strong> When bigrams won't work</a>
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<a "Part 05-Module 01-Lesson 06_Part of Speech Tagging with HMMs/06. Hidden Markov Models.html"><strong>Concept 06:</strong> Hidden Markov Models</a>
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<a "Part 05-Module 01-Lesson 06_Part of Speech Tagging with HMMs/07. Quiz How many paths.html"><strong>Concept 07:</strong> Quiz: How many paths?</a>
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<a "Part 05-Module 01-Lesson 06_Part of Speech Tagging with HMMs/08. Solution How many paths.html"><strong>Concept 08:</strong> Solution: How many paths</a>
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<a "Part 05-Module 01-Lesson 06_Part of Speech Tagging with HMMs/09. Quiz How many paths now.html"><strong>Concept 09:</strong> Quiz: How many paths now?</a>
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<a "Part 05-Module 01-Lesson 06_Part of Speech Tagging with HMMs/10. Quiz Which path is more likely.html"><strong>Concept 10:</strong> Quiz: Which path is more likely?</a>
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<a "Part 05-Module 01-Lesson 06_Part of Speech Tagging with HMMs/11. Solution Which path is more likely.html"><strong>Concept 11:</strong> Solution: Which path is more likely?</a>
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<a "Part 05-Module 01-Lesson 06_Part of Speech Tagging with HMMs/12. Viterbi Algorithm Idea.html"><strong>Concept 12:</strong> Viterbi Algorithm Idea</a>
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<a "Part 05-Module 01-Lesson 06_Part of Speech Tagging with HMMs/13. Viterbi Algorithm.html"><strong>Concept 13:</strong> Viterbi Algorithm</a>
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<a "Part 05-Module 01-Lesson 06_Part of Speech Tagging with HMMs/14. Further Reading.html"><strong>Concept 14:</strong> Further Reading</a>
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<a "Part 05-Module 01-Lesson 06_Part of Speech Tagging with HMMs/15. Outro.html"><strong>Concept 15:</strong> Outro</a>
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<summary>
<a "Part 05-Module 01-Lesson 07_Project Part of Speech Tagging/index.html"><strong>Lesson 07:</strong> Project: Part of Speech Tagging</a>
<p><p>In this project, you'll build a hidden Markov model for part of speech tagging with a universal tagset.</p></p>
<p><a "Part 05-Module 01-Lesson 07_Project Part of Speech Tagging/Project Description - Part of Speech Tagging.html">Project Description - Part of Speech Tagging</a></p>
<p><a "Part 05-Module 01-Lesson 07_Project Part of Speech Tagging/Project Rubric - Part of Speech Tagging.html">Project Rubric - Part of Speech Tagging</a></p>
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<a "Part 05-Module 01-Lesson 07_Project Part of Speech Tagging/01. Lesson Plan - Week 3.html"><strong>Concept 01:</strong> Lesson Plan - Week 3</a>
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<a "Part 05-Module 01-Lesson 07_Project Part of Speech Tagging/02. Introduction.html"><strong>Concept 02:</strong> Introduction</a>
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<a "Part 05-Module 01-Lesson 07_Project Part of Speech Tagging/03. Workspace Part of Speech Tagging.html"><strong>Concept 03:</strong> Workspace: Part of Speech Tagging</a>
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<summary>
<a "Part 05-Module 01-Lesson 08_(Optional) IBM Watson Bookworm Lab/index.html"><strong>Lesson 08:</strong> (Optional) IBM Watson Bookworm Lab</a>
<p><p>Learn how to build a simple question-answering agent using IBM Watson.</p></p>
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<a "Part 05-Module 01-Lesson 08_(Optional) IBM Watson Bookworm Lab/01. Overview.html"><strong>Concept 01:</strong> Overview</a>
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<a "Part 05-Module 01-Lesson 08_(Optional) IBM Watson Bookworm Lab/02. Getting Started.html"><strong>Concept 02:</strong> Getting Started</a>
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<a "Part 05-Module 01-Lesson 08_(Optional) IBM Watson Bookworm Lab/03. Tasks.html"><strong>Concept 03:</strong> Tasks</a>
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<a "Part 05-Module 01-Lesson 08_(Optional) IBM Watson Bookworm Lab/04. Workspace Bookworm.html"><strong>Concept 04:</strong> Workspace: Bookworm</a>
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<strong>Module 02:</strong> Career Services
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<details>
<summary>
<a "Part 05-Module 02-Lesson 01_Jobs in NLP/index.html"><strong>Lesson 01:</strong> Jobs in NLP</a>
<p><p>Learn about common jobs in natural language processing, and get tips on how to stay active in the community.</p></p>
</summary>
<ul>
<li>
<a "Part 05-Module 02-Lesson 01_Jobs in NLP/01. Jobs in NLP.html"><strong>Concept 01:</strong> Jobs in NLP</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 01_Jobs in NLP/02. Meet the Careers Team.html"><strong>Concept 02:</strong> Meet the Careers Team</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 01_Jobs in NLP/03. Access Your Career Portal.html"><strong>Concept 03:</strong> Access Your Career Portal</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 01_Jobs in NLP/04. Your Udacity Professional Profile.html"><strong>Concept 04:</strong> Your Udacity Professional Profile</a>
</li>
</ul>
</details>
</li>
<li>
<details>
<summary>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/index.html"><strong>Lesson 02:</strong> Optimize Your GitHub Profile</a>
<p><p>Other professionals are collaborating on GitHub and growing their network. Submit your profile to ensure your profile is on par with leaders in your field.</p></p>
<p><a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/Project Description - Optimize Your GitHub Profile.html">Project Description - Optimize Your GitHub Profile</a></p>
<p><a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/Project Rubric - Optimize Your GitHub Profile.html">Project Rubric - Optimize Your GitHub Profile</a></p>
</summary>
<ul>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/01. Prove Your Skills With GitHub.html"><strong>Concept 01:</strong> Prove Your Skills With GitHub</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/02. Introduction.html"><strong>Concept 02:</strong> Introduction</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/03. GitHub profile important items.html"><strong>Concept 03:</strong> GitHub profile important items</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/04. Good GitHub repository.html"><strong>Concept 04:</strong> Good GitHub repository</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/05. Interview with Art - Part 1.html"><strong>Concept 05:</strong> Interview with Art - Part 1</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/06. Identify fixes for example “bad” profile.html"><strong>Concept 06:</strong> Identify fixes for example “bad” profile</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/07. Quick Fixes #1.html"><strong>Concept 07:</strong> Quick Fixes #1</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/08. Quick Fixes #2.html"><strong>Concept 08:</strong> Quick Fixes #2</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/09. Writing READMEs with Walter.html"><strong>Concept 09:</strong> Writing READMEs with Walter</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/10. Interview with Art - Part 2.html"><strong>Concept 10:</strong> Interview with Art - Part 2</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/11. Commit messages best practices.html"><strong>Concept 11:</strong> Commit messages best practices</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/12. Reflect on your commit messages.html"><strong>Concept 12:</strong> Reflect on your commit messages</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/13. Participating in open source projects.html"><strong>Concept 13:</strong> Participating in open source projects</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/14. Interview with Art - Part 3.html"><strong>Concept 14:</strong> Interview with Art - Part 3</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/15. Participating in open source projects 2.html"><strong>Concept 15:</strong> Participating in open source projects 2</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/16. Starring interesting repositories.html"><strong>Concept 16:</strong> Starring interesting repositories</a>
</li>
<li>
<a "Part 05-Module 02-Lesson 02_Optimize Your GitHub Profile/17. Next Steps.html"><strong>Concept 17:</strong> Next Steps</a>
</li>
</ul>
</details>
</li>
</ul>
</li>
</ul>
</div>
<div>
<h4><strong>Part 06 :</strong> Computing with Natural Language</h4>
<p></p>
<ul>
<li>
<strong>Module 01:</strong> Computing with Natural Language
<ul>
<li>
<details>
<summary>
<a "Part 06-Module 01-Lesson 01_Feature extraction and embeddings/index.html"><strong>Lesson 01:</strong> Feature extraction and embeddings</a>
<p><p>Transform text using methods like Bag-of-Words, TF-IDF, Word2Vec and GloVE to extract features that you can use in machine learning models.</p></p>
</summary>
<ul>
<li>
<a "Part 06-Module 01-Lesson 01_Feature extraction and embeddings/01. Feature Extraction.html"><strong>Concept 01:</strong> Feature Extraction</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 01_Feature extraction and embeddings/02. Bag of Words.html"><strong>Concept 02:</strong> Bag of Words</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 01_Feature extraction and embeddings/03. TF-IDF.html"><strong>Concept 03:</strong> TF-IDF</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 01_Feature extraction and embeddings/04. One-Hot Encoding.html"><strong>Concept 04:</strong> One-Hot Encoding</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 01_Feature extraction and embeddings/05. Word Embeddings.html"><strong>Concept 05:</strong> Word Embeddings</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 01_Feature extraction and embeddings/06. Word2Vec.html"><strong>Concept 06:</strong> Word2Vec</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 01_Feature extraction and embeddings/07. GloVe.html"><strong>Concept 07:</strong> GloVe</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 01_Feature extraction and embeddings/08. Embeddings for Deep Learning.html"><strong>Concept 08:</strong> Embeddings for Deep Learning</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 01_Feature extraction and embeddings/09. t-SNE.html"><strong>Concept 09:</strong> t-SNE</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 01_Feature extraction and embeddings/10. Summary.html"><strong>Concept 10:</strong> Summary</a>
</li>
</ul>
</details>
</li>
<li>
<details>
<summary>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/index.html"><strong>Lesson 02:</strong> Topic Modeling</a>
<p><p>In this section, you'll learn to split a collection of documents into topics using Latent Dirichlet Analysis (LDA). In the lab, you'll be able to apply this model to a dataset of news articles.</p></p>
</summary>
<ul>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/01. Intro.html"><strong>Concept 01:</strong> Intro</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/02. References.html"><strong>Concept 02:</strong> References</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/03. Bag of Words.html"><strong>Concept 03:</strong> Bag of Words</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/04. Latent Variables.html"><strong>Concept 04:</strong> Latent Variables</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/05. Matrix Multiplication.html"><strong>Concept 05:</strong> Matrix Multiplication</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/06. Matrices.html"><strong>Concept 06:</strong> Matrices</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/07. Quiz Picking Topics.html"><strong>Concept 07:</strong> Quiz: Picking Topics</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/08. Solution Picking Topics.html"><strong>Concept 08:</strong> Solution: Picking Topics</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/09. Beta Distributions.html"><strong>Concept 09:</strong> Beta Distributions</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/10. Dirichlet Distributions.html"><strong>Concept 10:</strong> Dirichlet Distributions</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/11. Latent Dirichlet Allocation.html"><strong>Concept 11:</strong> Latent Dirichlet Allocation</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/12. Sample a Topic.html"><strong>Concept 12:</strong> Sample a Topic</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/13. Sample a Word.html"><strong>Concept 13:</strong> Sample a Word</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/14. Combining the Models.html"><strong>Concept 14:</strong> Combining the Models</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/15. Outro.html"><strong>Concept 15:</strong> Outro</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/16. Notebook Topic Modeling.html"><strong>Concept 16:</strong> Notebook: Topic Modeling</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/17. [SOLUTION] Topic Modeling.html"><strong>Concept 17:</strong> [SOLUTION] Topic Modeling</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 02_Topic Modeling/18. Next Steps.html"><strong>Concept 18:</strong> Next Steps</a>
</li>
</ul>
</details>
</li>
<li>
<details>
<summary>
<a "Part 06-Module 01-Lesson 03_Sentiment Analysis/index.html"><strong>Lesson 03:</strong> Sentiment Analysis</a>
<p><p>Learn about using several machine learning classifiers, including Recurrent Neural Networks, to predict the sentiment in text. Apply this to a dataset of movie reviews.</p></p>
</summary>
<ul>
<li>
<a "Part 06-Module 01-Lesson 03_Sentiment Analysis/01. Intro.html"><strong>Concept 01:</strong> Intro</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 03_Sentiment Analysis/02. Sentiment Analysis with a Regular Classifier.html"><strong>Concept 02:</strong> Sentiment Analysis with a Regular Classifier</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 03_Sentiment Analysis/03. Notebook Sentiment Analysis with a regular classifier.html"><strong>Concept 03:</strong> Notebook: Sentiment Analysis with a regular classifier</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 03_Sentiment Analysis/04. [SOLUTION] Sentiment Analysis with a regular clas.html"><strong>Concept 04:</strong> [SOLUTION]: Sentiment Analysis with a regular clas</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 03_Sentiment Analysis/05. Sentiment Analysis with RNN.html"><strong>Concept 05:</strong> Sentiment Analysis with RNN</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 03_Sentiment Analysis/06. Notebook Sentiment Analysis with an RNN.html"><strong>Concept 06:</strong> Notebook: Sentiment Analysis with an RNN</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 03_Sentiment Analysis/07. [SOLUTION] Sentiment Analysis with an RNN.html"><strong>Concept 07:</strong> [SOLUTION]: Sentiment Analysis with an RNN</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 03_Sentiment Analysis/08. Optional Material.html"><strong>Concept 08:</strong> Optional Material</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 03_Sentiment Analysis/09. Outro.html"><strong>Concept 09:</strong> Outro</a>
</li>
</ul>
</details>
</li>
<li>
<details>
<summary>
<a "Part 06-Module 01-Lesson 04_Sequence to Sequence/index.html"><strong>Lesson 04:</strong> Sequence to Sequence</a>
<p><p>Here you'll learn about a specific architecture of RNNs for generating one sequence from another sequence. These RNNs are useful for chatbots, machine translation, and more!</p></p>
</summary>
<ul>
<li>
<a "Part 06-Module 01-Lesson 04_Sequence to Sequence/01. Introducing Jay Alammar.html"><strong>Concept 01:</strong> Introducing Jay Alammar</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 04_Sequence to Sequence/02. Previous Material.html"><strong>Concept 02:</strong> Previous Material</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 04_Sequence to Sequence/03. Jay Introduction.html"><strong>Concept 03:</strong> Jay Introduction</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 04_Sequence to Sequence/04. Applications.html"><strong>Concept 04:</strong> Applications</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 04_Sequence to Sequence/05. Architectures.html"><strong>Concept 05:</strong> Architectures</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 04_Sequence to Sequence/06. Architectures in More Depth.html"><strong>Concept 06:</strong> Architectures in More Depth</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 04_Sequence to Sequence/07. Outro.html"><strong>Concept 07:</strong> Outro</a>
</li>
</ul>
</details>
</li>
<li>
<details>
<summary>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/index.html"><strong>Lesson 05:</strong> Deep Learning Attention</a>
<p><p>Attention is one of the most important recent innovations in deep learning. In this section, you'll learn attention, and you'll go over a basic implementation of it in the lab.</p></p>
</summary>
<ul>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/01. Introduction to Attention.html"><strong>Concept 01:</strong> Introduction to Attention</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/02. Sequence to Sequence Recap.html"><strong>Concept 02:</strong> Sequence to Sequence Recap</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/03. Encoding -- Attention Overview.html"><strong>Concept 03:</strong> Encoding -- Attention Overview</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/04. Decoding -- Attention Overview.html"><strong>Concept 04:</strong> Decoding -- Attention Overview</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/05. Attention Overview.html"><strong>Concept 05:</strong> Attention Overview</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/06. Attention Encoder.html"><strong>Concept 06:</strong> Attention Encoder</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/07. Attention Decoder.html"><strong>Concept 07:</strong> Attention Decoder</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/08. Attention Encoder Decoder.html"><strong>Concept 08:</strong> Attention Encoder & Decoder</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/09. Bahdanau and Luong Attention.html"><strong>Concept 09:</strong> Bahdanau and Luong Attention</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/10. Multiplicative Attention.html"><strong>Concept 10:</strong> Multiplicative Attention</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/11. Additive Attention.html"><strong>Concept 11:</strong> Additive Attention</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/12. Additive and Multiplicative Attention.html"><strong>Concept 12:</strong> Additive and Multiplicative Attention</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/13. Computer Vision Applications.html"><strong>Concept 13:</strong> Computer Vision Applications</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/14. NLP Application Google Neural Machine Translation.html"><strong>Concept 14:</strong> NLP Application: Google Neural Machine Translation</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/15. Other Attention Methods.html"><strong>Concept 15:</strong> Other Attention Methods</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/16. The Transformer and Self-Attention.html"><strong>Concept 16:</strong> The Transformer and Self-Attention</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/17. Notebook Attention Basics.html"><strong>Concept 17:</strong> Notebook: Attention Basics</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/18. [SOLUTION] Attention Basics.html"><strong>Concept 18:</strong> [SOLUTION]: Attention Basics</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 05_Deep Learning Attention/19. Outro.html"><strong>Concept 19:</strong> Outro</a>
</li>
</ul>
</details>
</li>
<li>
<details>
<summary>
<a "Part 06-Module 01-Lesson 06_RNN Keras Lab/index.html"><strong>Lesson 06:</strong> RNN Keras Lab</a>
<p><p>This section will prepare you for the Machine Translation project. Here you will get hands-on practice with RNNs in Keras.</p></p>
</summary>
<ul>
<li>
<a "Part 06-Module 01-Lesson 06_RNN Keras Lab/01. Intro.html"><strong>Concept 01:</strong> Intro</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 06_RNN Keras Lab/02. Machine Translation.html"><strong>Concept 02:</strong> Machine Translation</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 06_RNN Keras Lab/03. Deciphering Code with character-level RNNs.html"><strong>Concept 03:</strong> Deciphering Code with character-level RNNs</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 06_RNN Keras Lab/04. [SOLUTION] Deciphering code with character-level RNNs.html"><strong>Concept 04:</strong> [SOLUTION] Deciphering code with character-level RNNs</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 06_RNN Keras Lab/05. Congratulations!.html"><strong>Concept 05:</strong> Congratulations!</a>
</li>
</ul>
</details>
</li>
<li>
<details>
<summary>
<a "Part 06-Module 01-Lesson 07_Cloud Computing Setup Instructions/index.html"><strong>Lesson 07:</strong> Cloud Computing Setup Instructions</a>
<p><p>Overview of the steps to configure remote environment for GPU-accelerated training (Note: NLPND does not include AWS credits)</p></p>
</summary>
<ul>
<li>
<a "Part 06-Module 01-Lesson 07_Cloud Computing Setup Instructions/01. Overview.html"><strong>Concept 01:</strong> Overview</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 07_Cloud Computing Setup Instructions/02. Create an AWS Account.html"><strong>Concept 02:</strong> Create an AWS Account</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 07_Cloud Computing Setup Instructions/03. Get Access to GPU Instances.html"><strong>Concept 03:</strong> Get Access to GPU Instances</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 07_Cloud Computing Setup Instructions/04. Launch Your Instance.html"><strong>Concept 04:</strong> Launch Your Instance</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 07_Cloud Computing Setup Instructions/05. Remotely Connecting to Your Instance.html"><strong>Concept 05:</strong> Remotely Connecting to Your Instance</a>
</li>
</ul>
</details>
</li>
<li>
<details>
<summary>
<a "Part 06-Module 01-Lesson 08_Project Machine Translation/index.html"><strong>Lesson 08:</strong> Project: Machine Translation</a>
<p><p>Apply the skills you've learnt in Natural Language Processing to the challenging and extremely rewarding task of Machine Translation. <em>Bonne chance!</em></p></p>
<p><a "Part 06-Module 01-Lesson 08_Project Machine Translation/Project Description - Project Machine Translation.html">Project Description - Project: Machine Translation</a></p>
<p><a "Part 06-Module 01-Lesson 08_Project Machine Translation/Project Rubric - Project Machine Translation.html">Project Rubric - Project: Machine Translation</a></p>
</summary>
<ul>
<li>
<a "Part 06-Module 01-Lesson 08_Project Machine Translation/01. Introduction to GPU Workspaces.html"><strong>Concept 01:</strong> Introduction to GPU Workspaces</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 08_Project Machine Translation/02. Workspaces Best Practices.html"><strong>Concept 02:</strong> Workspaces: Best Practices</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 08_Project Machine Translation/03. NLP Machine Translation Workspace.html"><strong>Concept 03:</strong> NLP Machine Translation Workspace</a>
</li>
<li>
<a "Part 06-Module 01-Lesson 08_Project Machine Translation/04. Project Machine Translation.html"><strong>Concept 04:</strong> Project: Machine Translation</a>
</li>
</ul>
</details>
</li>
</ul>
</li>
<li>
<strong>Module 02:</strong> Career Services
<ul>
<li>
<details>
<summary>
<a "Part 06-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/index.html"><strong>Lesson 01:</strong> Strengthen Your Online Presence Using LinkedIn</a>
<p><p>Find your next job or connect with industry peers on LinkedIn. Ensure your profile attracts relevant leads that will grow your professional network.</p></p>
<p><a "Part 06-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/Project Description - Improve Your LinkedIn Profile.html">Project Description - Improve Your LinkedIn Profile</a></p>
<p><a "Part 06-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/Project Rubric - Improve Your LinkedIn Profile.html">Project Rubric - Improve Your LinkedIn Profile</a></p>
</summary>
<ul>
<li>
<a "Part 06-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/01. Get Opportunities with LinkedIn.html"><strong>Concept 01:</strong> Get Opportunities with LinkedIn</a>
</li>
<li>
<a "Part 06-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/02. Use Your Story to Stand Out.html"><strong>Concept 02:</strong> Use Your Story to Stand Out</a>
</li>
<li>
<a "Part 06-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/03. Why Use an Elevator Pitch.html"><strong>Concept 03:</strong> Why Use an Elevator Pitch</a>
</li>
<li>
<a "Part 06-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/04. Create Your Elevator Pitch.html"><strong>Concept 04:</strong> Create Your Elevator Pitch</a>
</li>
<li>
<a "Part 06-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/05. Use Your Elevator Pitch on LinkedIn.html"><strong>Concept 05:</strong> Use Your Elevator Pitch on LinkedIn</a>
</li>
<li>
<a "Part 06-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/06. Create Your Profile With SEO In Mind.html"><strong>Concept 06:</strong> Create Your Profile With SEO In Mind</a>
</li>
<li>
<a "Part 06-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/07. Profile Essentials.html"><strong>Concept 07:</strong> Profile Essentials</a>
</li>
<li>
<a "Part 06-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/08. Work Experiences Accomplishments.html"><strong>Concept 08:</strong> Work Experiences & Accomplishments</a>
</li>
<li>
<a "Part 06-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/09. Build and Strengthen Your Network.html"><strong>Concept 09:</strong> Build and Strengthen Your Network</a>
</li>
<li>
<a "Part 06-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/10. Reaching Out on LinkedIn.html"><strong>Concept 10:</strong> Reaching Out on LinkedIn</a>
</li>
<li>
<a "Part 06-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/11. Boost Your Visibility.html"><strong>Concept 11:</strong> Boost Your Visibility</a>
</li>
<li>
<a "Part 06-Module 02-Lesson 01_Strengthen Your Online Presence Using LinkedIn/12. Up Next.html"><strong>Concept 12:</strong> Up Next</a>
</li>
</ul>
</details>
</li>
</ul>
</li>
</ul>
</div>
<div>
<h4><strong>Part 07 :</strong> Communicating with Natural Language</h4>
<p></p>
<ul>
<li>
<strong>Module 01:</strong> Communicating in Natural Language
<ul>
<li>
<details>
<summary>
<a "Part 07-Module 01-Lesson 01_Intro to Voice User Interfaces/index.html"><strong>Lesson 01:</strong> Intro to Voice User Interfaces</a>
<p><p>Get acquainted with the principles and applications of VUI, and get introduced to Alexa skills.</p></p>
</summary>
<ul>
<li>
<a "Part 07-Module 01-Lesson 01_Intro to Voice User Interfaces/01. Welcome to Voice User Interfaces!.html"><strong>Concept 01:</strong> Welcome to Voice User Interfaces!</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 01_Intro to Voice User Interfaces/02. VUI Overview.html"><strong>Concept 02:</strong> VUI Overview</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 01_Intro to Voice User Interfaces/03. VUI Applications.html"><strong>Concept 03:</strong> VUI Applications</a>
</li>
</ul>
</details>
</li>
<li>
<details>
<summary>
<a "Part 07-Module 01-Lesson 02_(Optional) Alexa History Skill/index.html"><strong>Lesson 02:</strong> (Optional) Alexa History Skill</a>
<p><p>Build your own Alexa skill and deploy it!</p></p>
</summary>
<ul>
<li>
<a "Part 07-Module 01-Lesson 02_(Optional) Alexa History Skill/01. Overview.html"><strong>Concept 01:</strong> Overview</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 02_(Optional) Alexa History Skill/02. Getting Started.html"><strong>Concept 02:</strong> Getting Started</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 02_(Optional) Alexa History Skill/03. Tasks.html"><strong>Concept 03:</strong> Tasks</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 02_(Optional) Alexa History Skill/04. Deploying Your Skill.html"><strong>Concept 04:</strong> Deploying Your Skill</a>
</li>
</ul>
</details>
</li>
<li>
<details>
<summary>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/index.html"><strong>Lesson 03:</strong> Speech Recognition</a>
<p><p>Learn how an ASR pipeline works.</p></p>
</summary>
<ul>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/01. Intro.html"><strong>Concept 01:</strong> Intro</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/02. Challenges in ASR.html"><strong>Concept 02:</strong> Challenges in ASR</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/03. Signal Analysis.html"><strong>Concept 03:</strong> Signal Analysis</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/04. References Signal Analysis.html"><strong>Concept 04:</strong> References: Signal Analysis</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/05. Quiz FFT.html"><strong>Concept 05:</strong> Quiz: FFT</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/06. Feature Extraction with MFCC.html"><strong>Concept 06:</strong> Feature Extraction with MFCC</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/07. References Feature Extraction.html"><strong>Concept 07:</strong> References: Feature Extraction</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/08. Quiz MFCC.html"><strong>Concept 08:</strong> Quiz: MFCC</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/09. Phonetics.html"><strong>Concept 09:</strong> Phonetics</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/10. References Phonetics.html"><strong>Concept 10:</strong> References: Phonetics</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/11. Quiz Phonetics.html"><strong>Concept 11:</strong> Quiz: Phonetics</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/12. Voice Data Lab Introduction.html"><strong>Concept 12:</strong> Voice Data Lab Introduction</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/13. Lab Voice Data.html"><strong>Concept 13:</strong> Lab: Voice Data</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/14. Acoustic Models and the Trouble with Time.html"><strong>Concept 14:</strong> Acoustic Models and the Trouble with Time</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/15. HMMs in Speech Recognition.html"><strong>Concept 15:</strong> HMMs in Speech Recognition</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/16. Language Models.html"><strong>Concept 16:</strong> Language Models</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/17. N-Grams.html"><strong>Concept 17:</strong> N-Grams</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/18. Quiz N-Grams.html"><strong>Concept 18:</strong> Quiz: N-Grams</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/19. References Traditional ASR.html"><strong>Concept 19:</strong> References: Traditional ASR</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/20. A New Paradigm.html"><strong>Concept 20:</strong> A New Paradigm</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/21. Deep Neural Networks as Speech Models.html"><strong>Concept 21:</strong> Deep Neural Networks as Speech Models</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/22. Connectionist Tempora Classification (CTC).html"><strong>Concept 22:</strong> Connectionist Tempora Classification (CTC)</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/23. References Deep Neural Network ASR.html"><strong>Concept 23:</strong> References: Deep Neural Network ASR</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 03_Speech Recognition/24. Outro.html"><strong>Concept 24:</strong> Outro</a>
</li>
</ul>
</details>
</li>
<li>
<details>
<summary>
<a "Part 07-Module 01-Lesson 04_Project DNN Speech Recognizer/index.html"><strong>Lesson 04:</strong> Project: DNN Speech Recognizer</a>
<p><p>Build a deep neural network that functions as part of an end-to-end automatic speech recognition pipeline.</p></p>
<p><a "Part 07-Module 01-Lesson 04_Project DNN Speech Recognizer/Project Description - Project DNN Speech Recognizer.html">Project Description - Project: DNN Speech Recognizer</a></p>
<p><a "Part 07-Module 01-Lesson 04_Project DNN Speech Recognizer/Project Rubric - Project DNN Speech Recognizer.html">Project Rubric - Project: DNN Speech Recognizer</a></p>
</summary>
<ul>
<li>
<a "Part 07-Module 01-Lesson 04_Project DNN Speech Recognizer/01. Overview.html"><strong>Concept 01:</strong> Overview</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 04_Project DNN Speech Recognizer/02. Introduction to GPU Workspaces.html"><strong>Concept 02:</strong> Introduction to GPU Workspaces</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 04_Project DNN Speech Recognizer/03. Workspaces Best Practices.html"><strong>Concept 03:</strong> Workspaces: Best Practices</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 04_Project DNN Speech Recognizer/04. Tasks.html"><strong>Concept 04:</strong> Tasks</a>
</li>
<li>
<a "Part 07-Module 01-Lesson 04_Project DNN Speech Recognizer/05. VUI Speech Recognizer Workspace.html"><strong>Concept 05:</strong> VUI Speech Recognizer Workspace</a>
</li>
</ul>
</details>
</li>
</ul>
</li>
</ul>
</div>
<div>
<h4><strong>Part 08 <em>(Elective)</em>:</strong> Recurrent Neural Networks</h4>
<p></p>
<ul>
<li>
<strong>Module 01:</strong> Recurrent Neural Networks
<ul>
<li>
<details>
<summary>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/index.html"><strong>Lesson 01:</strong> Recurrent Neural Networks</a>
<p><p>Ortal will introduce Recurrent Neural Networks (RNNs), which are machine learning models that are able to recognize and act on sequences of inputs.</p></p>
</summary>
<ul>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/01. Introducing Ortal .html"><strong>Concept 01:</strong> Introducing Ortal </a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/02. RNN Introduction.html"><strong>Concept 02:</strong> RNN Introduction</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/03. RNN History.html"><strong>Concept 03:</strong> RNN History</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/04. RNN Applications.html"><strong>Concept 04:</strong> RNN Applications</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/05. Feedforward Neural Network-Reminder.html"><strong>Concept 05:</strong> Feedforward Neural Network-Reminder</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/06. The Feedforward Process.html"><strong>Concept 06:</strong> The Feedforward Process</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/07. Feedforward Quiz.html"><strong>Concept 07:</strong> Feedforward Quiz</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/08. Backpropagation- Theory.html"><strong>Concept 08:</strong> Backpropagation- Theory</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/09. Backpropagation - Example (part a).html"><strong>Concept 09:</strong> Backpropagation - Example (part a)</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/10. Backpropagation- Example (part b).html"><strong>Concept 10:</strong> Backpropagation- Example (part b)</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/11. Backpropagation Quiz.html"><strong>Concept 11:</strong> Backpropagation Quiz</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/12. RNN (part a).html"><strong>Concept 12:</strong> RNN (part a)</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/13. RNN (part b).html"><strong>Concept 13:</strong> RNN (part b)</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/14. RNN- Unfolded Model.html"><strong>Concept 14:</strong> RNN- Unfolded Model</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/15. Unfolded Model Quiz.html"><strong>Concept 15:</strong> Unfolded Model Quiz</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/16. RNN- Example.html"><strong>Concept 16:</strong> RNN- Example</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/17. Backpropagation Through Time (part a).html"><strong>Concept 17:</strong> Backpropagation Through Time (part a)</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/18. Backpropagation Through Time (part b).html"><strong>Concept 18:</strong> Backpropagation Through Time (part b)</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/19. Backpropagation Through Time (part c).html"><strong>Concept 19:</strong> Backpropagation Through Time (part c)</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/20. BPTT Quiz 1.html"><strong>Concept 20:</strong> BPTT Quiz 1</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/21. BPTT Quiz 2.html"><strong>Concept 21:</strong> BPTT Quiz 2</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/22. BPTT Quiz 3.html"><strong>Concept 22:</strong> BPTT Quiz 3</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/23. Some more math.html"><strong>Concept 23:</strong> Some more math</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/24. RNN Summary.html"><strong>Concept 24:</strong> RNN Summary</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/25. From RNN to LSTM.html"><strong>Concept 25:</strong> From RNN to LSTM</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 01_Recurrent Neural Networks/26. Wrap Up.html"><strong>Concept 26:</strong> Wrap Up</a>
</li>
</ul>
</details>
</li>
<li>
<details>
<summary>
<a "Part 08-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/index.html"><strong>Lesson 02:</strong> Long Short-Term Memory Networks (LSTM)</a>
<p><p>Luis explains Long Short-Term Memory Networks (LSTM), and similar architectures which have the benefits of preserving long term memory.</p></p>
</summary>
<ul>
<li>
<a "Part 08-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/01. Intro to LSTM.html"><strong>Concept 01:</strong> Intro to LSTM</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/02. RNN vs LSTM.html"><strong>Concept 02:</strong> RNN vs LSTM</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/03. Basics of LSTM.html"><strong>Concept 03:</strong> Basics of LSTM</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/04. Architecture of LSTM.html"><strong>Concept 04:</strong> Architecture of LSTM</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/05. The Learn Gate.html"><strong>Concept 05:</strong> The Learn Gate</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/06. The Forget Gate.html"><strong>Concept 06:</strong> The Forget Gate</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/07. The Remember Gate.html"><strong>Concept 07:</strong> The Remember Gate</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/08. The Use Gate.html"><strong>Concept 08:</strong> The Use Gate</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/09. Putting it All Together.html"><strong>Concept 09:</strong> Putting it All Together</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/10. Quiz.html"><strong>Concept 10:</strong> Quiz</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/11. Other architectures.html"><strong>Concept 11:</strong> Other architectures</a>
</li>
<li>
<a "Part 08-Module 01-Lesson 02_Long Short-Term Memory Networks (LSTM)/12. Outro LSTM.html"><strong>Concept 12:</strong> Outro LSTM</a>
</li>
</ul>
</details>
</li>
</ul>
</li>
</ul>
</div>
<div>
<h4><strong>Part 09 <em>(Elective)</em>:</strong> Keras</h4>
<p></p>
<ul>
<li>
<strong>Module 01:</strong> Keras
<ul>
<li>
<details>
<summary>
<a "Part 09-Module 01-Lesson 01_Keras/index.html"><strong>Lesson 01:</strong> Keras</a>
<p><p>In this section you'll get a hands-on introduction to Keras. You'll learn to apply it to analyze movie reviews.</p></p>
</summary>
<ul>
<li>
<a "Part 09-Module 01-Lesson 01_Keras/01. Intro.html"><strong>Concept 01:</strong> Intro</a>
</li>
<li>
<a "Part 09-Module 01-Lesson 01_Keras/02. Keras.html"><strong>Concept 02:</strong> Keras</a>
</li>
<li>
<a "Part 09-Module 01-Lesson 01_Keras/03. Pre-Lab Student Admissions in Keras.html"><strong>Concept 03:</strong> Pre-Lab: Student Admissions in Keras</a>
</li>
<li>
<a "Part 09-Module 01-Lesson 01_Keras/04. Lab Student Admissions in Keras.html"><strong>Concept 04:</strong> Lab: Student Admissions in Keras</a>
</li>
<li>
<a "Part 09-Module 01-Lesson 01_Keras/05. Optimizers in Keras.html"><strong>Concept 05:</strong> Optimizers in Keras</a>
</li>
<li>
<a "Part 09-Module 01-Lesson 01_Keras/06. Mini Project Intro.html"><strong>Concept 06:</strong> Mini Project Intro</a>
</li>
<li>
<a "Part 09-Module 01-Lesson 01_Keras/07. Pre-Lab IMDB Data in Keras.html"><strong>Concept 07:</strong> Pre-Lab: IMDB Data in Keras</a>
</li>
<li>
<a "Part 09-Module 01-Lesson 01_Keras/08. Lab IMDB Data in Keras.html"><strong>Concept 08:</strong> Lab: IMDB Data in Keras</a>
</li>
</ul>
</details>
</li>
</ul>
</li>
</ul>
</div>
<div>
<h4><strong>Part 10 <em>(Elective)</em>:</strong> Sentiment Analysis Extras</h4>
<p></p>
<ul>
<li>
<strong>Module 01:</strong> Sentiment Analysis
<ul>
<li>
<details>
<summary>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/index.html"><strong>Lesson 01:</strong> Sentiment Analysis with Andrew Trask</a>
</summary>
<ul>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/01. Meet Andrew.html"><strong>Concept 01:</strong> Meet Andrew</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/02. Materials.html"><strong>Concept 02:</strong> Materials</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/03. The Notebooks.html"><strong>Concept 03:</strong> The Notebooks</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/04. Framing the Problem.html"><strong>Concept 04:</strong> Framing the Problem</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/05. Mini Project 1.html"><strong>Concept 05:</strong> Mini Project 1</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/06. Mini Project 1 Solution.html"><strong>Concept 06:</strong> Mini Project 1 Solution</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/07. Transforming Text into Numbers.html"><strong>Concept 07:</strong> Transforming Text into Numbers</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/08. Mini Project 2.html"><strong>Concept 08:</strong> Mini Project 2</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/09. Mini Project 2 Solution.html"><strong>Concept 09:</strong> Mini Project 2 Solution</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/10. Building a Neural Network.html"><strong>Concept 10:</strong> Building a Neural Network</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/11. Mini Project 3.html"><strong>Concept 11:</strong> Mini Project 3</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/12. Mini Project 3 Solution.html"><strong>Concept 12:</strong> Mini Project 3 Solution</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/13. Understanding Neural Noise.html"><strong>Concept 13:</strong> Understanding Neural Noise</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/14. Mini Project 4.html"><strong>Concept 14:</strong> Mini Project 4</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/15. Understanding Inefficiencies in our Network.html"><strong>Concept 15:</strong> Understanding Inefficiencies in our Network</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/16. Mini Project 5.html"><strong>Concept 16:</strong> Mini Project 5</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/17. Mini Project 5 Solution.html"><strong>Concept 17:</strong> Mini Project 5 Solution</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/18. Further Noise Reduction.html"><strong>Concept 18:</strong> Further Noise Reduction</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/19. Mini Project 6.html"><strong>Concept 19:</strong> Mini Project 6</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/20. Mini Project 6 Solution.html"><strong>Concept 20:</strong> Mini Project 6 Solution</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/21. Analysis What's Going on in the Weights.html"><strong>Concept 21:</strong> Analysis: What's Going on in the Weights?</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 01_Sentiment Analysis with Andrew Trask/22. Conclusion.html"><strong>Concept 22:</strong> Conclusion</a>
</li>
</ul>
</details>
</li>
<li>
<details>
<summary>
<a "Part 10-Module 01-Lesson 02_Sentiment Prediction RNN/index.html"><strong>Lesson 02:</strong> Sentiment Prediction RNN</a>
<p><p>Implement a sentiment prediction RNN</p></p>
</summary>
<ul>
<li>
<a "Part 10-Module 01-Lesson 02_Sentiment Prediction RNN/01. Intro.html"><strong>Concept 01:</strong> Intro</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 02_Sentiment Prediction RNN/02. Sentiment RNN.html"><strong>Concept 02:</strong> Sentiment RNN</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 02_Sentiment Prediction RNN/03. Data Preprocessing.html"><strong>Concept 03:</strong> Data Preprocessing</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 02_Sentiment Prediction RNN/04. Creating Testing Sets.html"><strong>Concept 04:</strong> Creating Testing Sets</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 02_Sentiment Prediction RNN/05. Building the RNN.html"><strong>Concept 05:</strong> Building the RNN</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 02_Sentiment Prediction RNN/06. Training the Network.html"><strong>Concept 06:</strong> Training the Network</a>
</li>
<li>
<a "Part 10-Module 01-Lesson 02_Sentiment Prediction RNN/07. Solutions.html"><strong>Concept 07:</strong> Solutions</a>
</li>
</ul>
</details>
</li>
</ul>
</li>
</ul>
</div>
<div>
<h4><strong>Part 11 <em>(Elective)</em>:</strong> TensorFlow</h4>
<p></p>
<ul>
<li>
<strong>Module 01:</strong> TensorFlow
<ul>
<li>
<details>
<summary>
<a "Part 11-Module 01-Lesson 01_TensorFlow/index.html"><strong>Lesson 01:</strong> TensorFlow</a>
<p><p>In this section you'll get a hands-on introduction to TensorFlow, Google's deep learning framework, and you'll be able to apply it on an image dataset.</p></p>
</summary>
<ul>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/01. Intro.html"><strong>Concept 01:</strong> Intro</a>
</li>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/02. Installing TensorFlow.html"><strong>Concept 02:</strong> Installing TensorFlow</a>
</li>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/03. Hello, Tensor World!.html"><strong>Concept 03:</strong> Hello, Tensor World!</a>
</li>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/04. Quiz TensorFlow Linear Function.html"><strong>Concept 04:</strong> Quiz: TensorFlow Linear Function</a>
</li>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/05. Quiz TensorFlow Softmax.html"><strong>Concept 05:</strong> Quiz: TensorFlow Softmax</a>
</li>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/06. Quiz TensorFlow Cross Entropy.html"><strong>Concept 06:</strong> Quiz: TensorFlow Cross Entropy</a>
</li>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/07. Quiz Mini-batch.html"><strong>Concept 07:</strong> Quiz: Mini-batch</a>
</li>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/08. Epochs.html"><strong>Concept 08:</strong> Epochs</a>
</li>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/09. Pre-Lab NotMNIST in TensorFlow.html"><strong>Concept 09:</strong> Pre-Lab: NotMNIST in TensorFlow</a>
</li>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/10. Lab NotMNIST in TensorFlow.html"><strong>Concept 10:</strong> Lab: NotMNIST in TensorFlow</a>
</li>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/11. Two-layer Neural Network.html"><strong>Concept 11:</strong> Two-layer Neural Network</a>
</li>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/12. Quiz TensorFlow ReLUs.html"><strong>Concept 12:</strong> Quiz: TensorFlow ReLUs</a>
</li>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/13. Deep Neural Network in TensorFlow.html"><strong>Concept 13:</strong> Deep Neural Network in TensorFlow</a>
</li>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/14. Save and Restore TensorFlow Models.html"><strong>Concept 14:</strong> Save and Restore TensorFlow Models</a>
</li>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/15. Finetuning.html"><strong>Concept 15:</strong> Finetuning</a>
</li>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/16. Quiz TensorFlow Dropout.html"><strong>Concept 16:</strong> Quiz: TensorFlow Dropout</a>
</li>
<li>
<a "Part 11-Module 01-Lesson 01_TensorFlow/17. Outro.html"><strong>Concept 17:</strong> Outro</a>
</li>
</ul>
</details>
</li>
</ul>
</li>
</ul>
</div>
<div>
<h4><strong>Part 12 <em>(Elective)</em>:</strong> Embeddings and Word2Vec</h4>
<p></p>
<ul>
<li>
<strong>Module 01:</strong> Embeddings and Word2Vec
<ul>
<li>
<details>
<summary>
<a "Part 12-Module 01-Lesson 01_Embeddings and Word2Vec/index.html"><strong>Lesson 01:</strong> Embeddings and Word2Vec</a>
<p><p>In this lesson, you'll learn about embeddings in neural networks by implementing the word2vec model.</p></p>
</summary>
<ul>
<li>
<a "Part 12-Module 01-Lesson 01_Embeddings and Word2Vec/01. Additional NLP Lessons.html"><strong>Concept 01:</strong> Additional NLP Lessons</a>
</li>
<li>
<a "Part 12-Module 01-Lesson 01_Embeddings and Word2Vec/02. Embeddings Intro.html"><strong>Concept 02:</strong> Embeddings Intro</a>
</li>
<li>
<a "Part 12-Module 01-Lesson 01_Embeddings and Word2Vec/03. Implementing Word2Vec.html"><strong>Concept 03:</strong> Implementing Word2Vec</a>
</li>
<li>
<a "Part 12-Module 01-Lesson 01_Embeddings and Word2Vec/04. Subsampling Solution.html"><strong>Concept 04:</strong> Subsampling Solution</a>
</li>
<li>
<a "Part 12-Module 01-Lesson 01_Embeddings and Word2Vec/05. Making Batches.html"><strong>Concept 05:</strong> Making Batches</a>
</li>
<li>
<a "Part 12-Module 01-Lesson 01_Embeddings and Word2Vec/06. Batches Solution.html"><strong>Concept 06:</strong> Batches Solution</a>
</li>
<li>
<a "Part 12-Module 01-Lesson 01_Embeddings and Word2Vec/07. Building the Network.html"><strong>Concept 07:</strong> Building the Network</a>
</li>
<li>
<a "Part 12-Module 01-Lesson 01_Embeddings and Word2Vec/08. Negative Sampling.html"><strong>Concept 08:</strong> Negative Sampling</a>
</li>
<li>
<a "Part 12-Module 01-Lesson 01_Embeddings and Word2Vec/09. Building the Network Solution.html"><strong>Concept 09:</strong> Building the Network Solution</a>
</li>
<li>
<a "Part 12-Module 01-Lesson 01_Embeddings and Word2Vec/10. Training Results.html"><strong>Concept 10:</strong> Training Results</a>
</li>
</ul>
</details>
</li>
</ul>
</li>
</ul>
</div>
<div>
<h4><strong>Part 13 <em>(FreePreview)</em>:</strong> Project</h4>
<p></p>
<ul>
<li>
<strong>Module 01:</strong> Project
<ul>
<li>
<details>
<summary>
<a "Part 13-Module 01-Lesson 01_Project Part of Speech Tagging/index.html"><strong>Lesson 01:</strong> Project: Part of Speech Tagging</a>
<p><p>In this project, you'll build a hidden Markov model for part of speech tagging with a universal tagset.</p></p>
<p><a "Part 13-Module 01-Lesson 01_Project Part of Speech Tagging/Project Description - Part of Speech Tagging.html">Project Description - Part of Speech Tagging</a></p>
<p><a "Part 13-Module 01-Lesson 01_Project Part of Speech Tagging/Project Rubric - Part of Speech Tagging.html">Project Rubric - Part of Speech Tagging</a></p>
</summary>
<ul>
<li>
<a "Part 13-Module 01-Lesson 01_Project Part of Speech Tagging/01. Introduction.html"><strong>Concept 01:</strong> Introduction</a>
</li>
</ul>
</details>
</li>
</ul>
</li>
</ul>
</div>
</div>
</div>
</div>
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