# Deep_Learning

**Repository Path**: zhengHhan/Deep_Learning

## Basic Information

- **Project Name**: Deep_Learning
- **Description**: added all materials
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-09-21
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

* This is my assignment on Andrew Ng's special course  "[***Deep Learning Specialization***](https://www.coursera.org/specializations/deep-learning)" This course consists of five courses: 
    * [***Neural Networks and Deep Learning***](https://www.coursera.org/learn/neural-networks-deep-learning/home/welcome)  
    * [***Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization***](https://www.coursera.org/learn/deep-neural-network/home/welcome) 
    * [***Structuring Machine Learning Projects***](https://www.coursera.org/learn/machine-learning-projects/home/welcome)
    * [***Convolutional Neural Networks***](https://www.coursera.org/learn/convolutional-neural-networks)
    * [***Sequence Models***](https://www.coursera.org/learn/nlp-sequence-models)

![Neural Networks for Machine Learning](https://user-images.githubusercontent.com/21110541/29741101-6c274534-8a66-11e7-9e69-d3f2a362af8d.png)

![Improving Deep Neural Networks_Hyperparameter Tuning_Regularization and Optimization](https://user-images.githubusercontent.com/21110541/30242116-bd3cb3b6-9590-11e7-9621-aa30536d1a35.PNG)

![structuring machine learning projects](https://user-images.githubusercontent.com/21110541/30242472-5662a950-9597-11e7-9766-dc1c5816cde2.PNG)

![convolutional neural networks](https://user-images.githubusercontent.com/21110541/32508421-8cbe3448-c3ea-11e7-8743-e55c878ba0a7.PNG)

![sequence models](https://user-images.githubusercontent.com/21110541/36073520-35d04bc6-0f58-11e8-8f2e-a5c0c0752ae7.PNG)

# Deep Learning
+ [x] Neural Networks and Deep Learning
+ [x] Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
+ [x] Structuring Machine Learning Projects
+ [x] Convolutional Neural Networks
+ [x] Sequence Models

# Deep Learning - deeplearning.ai
Coursera Deep Learning Course by deeplearning.ai projects 

 ## Course 1. Neural Networks and Deep Learning
1. Week1 - Introduction to deep learning
2. Week2 - Neural Networks Basics
3. Week3 - Shallow neural networks
4. Week4 - Deep Neural Networks

## Course 2. Improving Deep Neural Networks Hyperparameter tuning, Regularization and Optimization
1. Week1 - Practical aspects of Deep Learning
         - Setting up your Machine Learning Application
         - Regularizing your neural network
         - Setting up your optimization problem
2. Week2 - Optimization algorithms
3. Week3 - Hyperparameter tuning, Batch Normalization and Programming Frameworks

## Course 3. Structuring Machine Learning Projects
1. Week1 - Introduction to ML Strategy
         - Setting up your goal
         - Comparing to human-level performance
2. Week2 - ML Strategy (2)
         - Error Analysis
         - Mismatched training and dev/test set
         - Learning from multiple tasks
         - End-to-end deep learning
         
 ## Course 4. Convolutional Neural Networks
 1. Week1 - Foundations of Convolutional Neural Networks
 2. Week2 - Deep convolutional models: case studies
 3. Week3 - Object detection - Papers for read: [You Only Look Once:
Unified, Real-Time Object Detection](https://arxiv.org/pdf/1506.02640.pdf), [YOLO](https://arxiv.org/pdf/1612.08242.pdf)
 4. Week4 - Special applications: Face recognition & Neural style transfer - Papers for read: [DeepFace](https://www.cs.toronto.edu/~ranzato/publications/taigman_cvpr14.pdf), [FaceNet](https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Schroff_FaceNet_A_Unified_2015_CVPR_paper.pdf)
 
 ## Course 5. Sequence Models
 1. Week1 - Recurrent Neural Networks
 2. Week2 - Natural Language Processing & Word Embeddings
 3. Week3 - Sequence models & Attention mechanism

---
*source from **Andrew Ng**'s [Deep learning](https://www.coursera.org/specializations/deep-learning) course on Coursera*