# IndexOfRepository **Repository Path**: coracoding/IndexOfRepository ## Basic Information - **Project Name**: IndexOfRepository - **Description**: No description available - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2020-03-26 - **Last Updated**: 2020-12-19 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # __IndexOfRepository index of repository ## include all repository by categories: ## compatitions: > * ### [A collection of popular Data Science Competitions](https://github.com/iphysresearch/DataSciComp.git) > * #### [Kaggle 项目实战（教程） = 文档 + 代码 + 视频](https://github.com/DavidGPHub/kaggle) > * #### [AI Challenger, Baseline. https://challenger.ai/](https://github.com/DavidGPHub/AI_Challenger_2018.git) ## compatitions opensource solutions: > * #### [马上AI全球挑战赛-违约用户风险预测 2th](https://github.com/DavidGPHub/AI-challenger-contest.git) > * #### [FDDCprocess](https://github.com/DavidGPHub/FDDCprocess.git) > * #### [1st Place Solution for O2O Coupon Usage Forecast](https://github.com/DavidGPHub/O2O-Coupon-Usage-Forecast.git) > * #### [Data competition Top Solution 数据竞赛top解决方案开源整理](https://github.com/Smilexuhc/Data-Competition-TopSolution.git) > * #### [CCF-大数据竞赛-基金间的相关性预测-复赛19名 ](https://github.com/DavidGPHub/CCF-bigdata.git) ## class/books and roadmap: > * ### [自上而下的学习路线: 软件工程师的机器学习 machine-learning-for-software-engineers](https://github.com/DavidGPHub/machine-learning-for-software-engineers.git) > * #### [Deep Learning 中文翻译 deeplearningbook-chinese](https://github.com/DavidGPHub/deeplearningbook-chinese.git) > * #### [《神经网络与深度学习》 Neural Network and Deep Learning](https://github.com/nndl/nndl.github.io.git) > * #### [深度学习/人工智能/机器学习资料汇总(Deep Learning/Artificial Intelligent/Machine Learning) 持续更新……](https://github.com/Robinwho/Deep-Learning.git) > * #### [10 Steps to Become a Data Scientist](https://github.com/mjbahmani/10-steps-to-become-a-data-scientist.git) > * #### [机器学习专项领域学习 ](https://github.com/JustFollowUs/Machine-Learning.git) ## machine learning: > * #### [AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP http://ailearning.apachecn.org/](https://github.com/DavidGPHub/AiLearning.git) > * #### [cs229 learning camp/吴恩达在斯坦福的机器学习课](https://github.com/DavidGPHub/cs229-learning-camp.git) > * #### [吴恩达老师的机器学习课程个人笔记](https://github.com/fengdu78/Coursera-ML-AndrewNg-Notes.git) > * #### [吴恩达老师的深度学习课（deepLearning.ai）的笔记](https://github.com/fengdu78/deeplearning_ai_books) > * #### [CS229 Machine Learning Assignments in Python](https://github.com/DavidGPHub/cs229-assignments.git) > * #### [A Chinese Translation of Stanford CS229 notes 斯坦福机器学习CS229课程讲义的中文翻译 https://zhuanlan.zhihu.com/python-kivy](https://github.com/DavidGPHub/Stanford-CS-229-CN.git) > * #### [机器学习(Machine Learning)&深度学习(Deep Learning)资料(Chapter 2)](https://github.com/ty4z2008/Qix/blob/master/dl2.md) > * #### [机器学习特征工程实用技巧大全](https://zhuanlan.zhihu.com/p/26444240) > * #### [深度有趣 - 人工智能实战项目合集](https://github.com/Honlan/DeepInterests.git) > * #### [MLFlow - Open source platform for the machine learning lifecycle https://mlflow.org](https://github.com/mlflow/mlflow.git) ## AutoML: > * #### [Google Cloud Client Library for Python https://googlecloudplatform.github.io…](https://github.com/googleapis/google-cloud-python/tree/master/automl) >> Notes, scripts and codes related to Google's AutoML https://cloud.google.com/automl/ > * #### [Google: Fast and flexible AutoML with learning guarantees.](https://github.com/tensorflow/adanet.git) >> 轻量级 AutoML 框架 —— AdaNet，该框架基于 TensorFlow，只需要少量的专家干预便能自动学习高质量模型，在提供学习保证（learning guarantee）的同时也能保持快速、灵活。值得一提的是，AdaNet 提供了一种通用框架，不仅能够学习神经网络架构，还能学习集成从而获得更佳的模型。 > * #### [H2O.ai -- Fast Scalable Machine Learning For Smarter Applications](https://github.com/h2oai) > * #### [MLeap: Deploy Spark Pipelines to Production http://mleap-docs.combust.ml/](https://github.com/combust/mleap.git) ## deep learning: > * #### [ Tensorflow: An Open Source Machine Learning Framework for Everyone https://tensorflow.org](https://github.com/DavidGPHub/tensorflow.git) > * #### [ TensorFlow - A curated list of dedicated resources http://tensorflow.org](https://github.com/DavidGPHub/awesome-tensorflow.git) > * #### [OpenAI: A toolkit for developing and comparing reinforcement learning algorithms. https://gym.openai.com/](https://github.com/DavidGPHub/gym.git) > * #### [TensorFlow on YARN (TonY) is a framework to natively run TensorFlow on Apache Hadoop.](https://github.com/DavidGPHub/TonY.git) > * #### [Qihoo360 AI on Hadoop: XLearning是一款支持多种机器学习、深度学习框架的调度系统。基于Hadoop Yarn完成了对TensorFlow、MXNet、Caffe、Theano、PyTorch、Keras、XGBoost等常用框架的集成，同时具备良好的扩展性和兼容性。](https://github.com/DavidGPHub/XLearning.git) > * #### [LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data](https://github.com/DavidGPHub/LSTM-Neural-Network-for-Time-Series-Prediction.git) > * #### [My tensorflow implementation of "A neural conversational model", a Deep learning based chatbot](https://github.com/DavidGPHub/DeepQA.git) > * #### [基于深度强化学习的资源调度研究](https://github.com/DavidGPHub/deeprm_reforement_learning.git) > * #### [DeepCreamPy 项目，它可以自动修复漫画图像中的空缺部分和马赛克。该项目主要基于几个月前 Nvidia 提出使用部分卷积修复图像不规则空缺的研究。](https://github.com/DavidGPHub/DeepCreamPy.git) > * #### [深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者](https://github.com/scutan90/DeepLearning-500-questions.git) > * #### [ 586 leaderboards • 993 tasks • 749 datasets • 9611 papers with code ](https://paperswithcode.com/sota) ## Tensorflow: > * #### [Zhihu tensorflow机器学习中文入门资源汇总](https://zhuanlan.zhihu.com/p/34922745) > * #### [ 简单粗暴TensorFlow](https://tf.wiki/zh/basic.html) > * #### [Tensorflow.org 开始使用 TensorFlow](https://www.tensorflow.org/tutorials/?hl=zh-cn) > * #### [TensorFlow Tutorials with YouTube Videos](https://github.com/Hvass-Labs/TensorFlow-Tutorials.git) ## deep learning benchmark: > * #### [Reference implementations of MLPerf benchmarks](https://github.com/DavidGPHub/reference.git) > * #### [SQuAD leaderboard](https://rajpurkar.github.io/SQuAD-explorer/) > * #### [DeepLearning DataSet List](https://rodrigob.github.io/are_we_there_yet/build/) > * #### [An End-to-End Deep Learning Benchmark and Competition](https://github.com/stanford-futuredata/dawn-bench-entries.git) (https://dawn.cs.stanford.edu/benchmark/) ## deep learning env in docker: > * #### [A series of Docker images (and their generator) that allows you to quickly set up your deep learning research environment.](https://github.com/DavidGPHub/deepo.git) (https://hub.docker.com/r/ufoym/deepo) ## NLP related: > * #### [Tracking Progress in Natural Language Processing](https://github.com/sebastianruder/NLP-progress.git) > * #### [100+ Chinese Word Vectors 上百种预训练中文词向量](https://github.com/DavidGPHub/Chinese-Word-Vectors.git) > * #### [深度学习之自然语言处理斯坦福大学CS224n课程集训营](https://github.com/DavidGPHub/cs224n-learning-camp.git) > * #### [腾讯开源中文词向量 Tencent AI Lab Embedding Corpus for Chinese Words and Phrases](https://ai.tencent.com/ailab/nlp/embedding.html) >> (https://ai.tencent.com/ailab/nlp/data/Tencent_AILab_ChineseEmbedding.tar.gz) > * #### [gensim – Topic Modelling in Python](https://github.com/DavidGPHub/gensim.git) > * #### [自然语言处理 中文分词 词性标注 命名实体识别 依存句法分析 关键词提取 新词发现 短语提取 自动摘要 文本分类 拼音简繁](https://github.com/DavidGPHub/HanLP.git) (http://hanlp.com/) > * #### [CS 4650 and 7650](https://github.com/DavidGPHub/gt-nlp-class.git) > * #### [Google : TensorFlow code and pre-trained models for BERT https://arxiv.org/abs/1810.04805](https://github.com/DavidGPHub/bert.git) > * #### [MatchZoo is a toolkit for text matching. It was developed to facilitate the designing, comparing, and sharing of deep text matching models.](https://github.com/DavidGPHub/MatchZoo.git) ## image related: > * #### [Largest multi-label image database; ResNet-101 model; 80.73% top-1 acc on ImageNet](https://github.com/DavidGPHub/tencent-ml-images.git) > * #### [Face recognition using Tensorflow](https://github.com/DavidGPHub/facenet.git) ## Spark: > * #### [Mastering Apache Spark 2, https://jaceklaskowski.gitbooks.io/mastering-apache-spark/](https://github.com/DavidGPHub/mastering-apache-spark-book.git) ## comment tools: > * #### [Python3 DHT 网络磁力种子采集器](https://github.com/DavidGPHub/magnet-dht.git) > * #### [webkettle平台，创造性的将平台构建为B/S架构的ETL模型设计以及集成用户专业调度管理的分布式ETL建模运维系统。](https://github.com/DavidGPHub/kettle.git) > * #### [Mirror of Apache Hadoop](https://github.com/DavidGPHub/hadoop-1.git) > * #### [fxdayu_alphaman:股票多因子策略开发框架](https://github.com/DavidGPHub/fxdayu_alphaman.git) ## resource allocation Algorithm: > * #### [efficient-resource-allocations](https://github.com/DavidGPHub/efficient-resource-allocations.git) > * #### [A Genetic Algorithm for the Stochastic Resource Constrained Project Scheduling Problem](https://github.com/DavidGPHub/Genetic-SRCPSP.git) ## docker: > * #### [Software-Defined Networking tools for LXC (LinuX Containers)](https://github.com/DavidGPHub/pipework.git) ## blockchain: > * #### [ book to introduce blockchain related techniques.](https://github.com/DavidGPHub/blockchain_guide.git) > * #### [https://yeasy.gitbooks.io/blockchain_guide](https://yeasy.gitbooks.io/blockchain_guide) > * #### [Solidity 中文文档](https://github.com/apachecn/solidity-doc-zh) > * #### [20170420（IBM微讲堂）区块链和HyperLedger系列（1-6）](https://www.jianshu.com/p/1c7492c42581) > * #### [https://yeasy.gitbooks.io/blockchain_guide](https://yeasy.gitbooks.io/blockchain_guide) ## interview related: > * #### [LeetCode with Python 算法相关知识储备 ](https://github.com/DavidGPHub/leetCode.git) > * #### [Leetcode 题解 (跟随思路一步一步撸出代码) 及经典算法实现](https://github.com/DavidGPHub/awesome-algorithm.git) > * #### [LeetCode：高效的代码、简洁的注释、精炼的总结。](https://github.com/DavidGPHub/LeetCode-1.git) > * #### [LeetCode 中文文档](https://github.com/apachecn/LeetCode) > * ### [2018/2019/算法/(Machine Learning)/(Deep Learning)/(NLP)/C/C++/Python/面试笔记](https://github.com/DavidGPHub/Algorithm_Interview_Notes-Chinese.git) > * #### [A list of back-end related questions you can be inspired from to interview potential candidates](https://github.com/DavidGPHub/Back-End-Developer-Interview-Questions.git) > * ### [Google Interview University 一套完整的学习手册帮助自己准备 Google 的面试](https://github.com/DavidGPHub/coding-interview-university.git) ## Spark: > * #### [Mastering Apache Spark 2, https://jaceklaskowski.gitbooks.io/mastering-apache-spark/](https://jaceklaskowski.gitbooks.io/mastering-apache-spark/) ## ApacheCN index: > * #### [ApacheCN 开源组织 http://www.apachecn.org](https://github.com/DavidGPHub/home.git) > 大数据 >> 1. [Spark 中文文档](https://github.com/apachecn/spark-doc-zh) >> 2. [Storm 中文文档](https://github.com/apachecn/storm-doc-zh) >> 3. [Kafka 中文文档](https://github.com/apachecn/kafka-doc-zh) >> 4. [Flink 中文文档](https://github.com/apachecn/flink-doc-zh) >> 5. [Beam 中文文档](https://github.com/apachecn/beam-site-zh) >> 6. [Zeppelin 0.7.2 中文文档](http://cwiki.apachecn.org/pages/viewpage.action?pageId=10030467) >> 7. [Elasticsearch 5.4 中文文档](http://cwiki.apachecn.org/pages/viewpage.action?pageId=4260364) >> 8. [Kibana 5.2 中文文档](http://cwiki.apachecn.org/pages/viewpage.action?pageId=8159377) >> 9. [Kudu 1.4.0 中文文档](http://cwiki.apachecn.org/pages/viewpage.action?pageId=10813594) > 数学笔记 >> 1. [MIT 18.06 线性代数笔记](https://github.com/apachecn/math) >> 2. [UCB Prob140 讲义：面向数据科学的概率论](https://github.com/apachecn/prob140-textbook-zh) >> 3. [fast.ai 数值线性代数讲义 v2](https://github.com/apachecn/fastai-num-linalg-v2-zh) > Python 基础 >> [numpy 中文文档](https://github.com/apachecn/numpy-ref-zh) >> [pandas 中文文档](https://github.com/apachecn/pandas-doc-zh) >> [matplotlib 中文文档](https://github.com/apachecn/matplotlib-user-guide-zh) > CS 教程 1. [GeeksForGeeks 翻译计划](https://github.com/apachecn/geeksforgeeks-zh) > AI 教程 1. [Machine Learning in Action - 机器学习实战（已追加部分 自然语言处理+深度学习 相关内容）](https://github.com/apachecn/AiLearning) 2. [Python 数据分析与挖掘实战（带注释源码）](https://github.com/apachecn/python_data_analysis_and_mining_action) 3. [SciPyCon 2018 Sklearn 教程](https://github.com/apachecn/scipycon-2018-sklearn-tut-zh) 4. [TensorFlow 学习指南](https://github.com/apachecn/learning-tf-zh) 5. [fast.ai 机器学习和深度学习中文笔记](https://github.com/apachecn/fastai-ml-dl-notes-zh) 6. [HackCV 网站文章翻译](https://github.com/apachecn/HackCV-Translate) > AI 文档 1. [sklearn 中文文档](https://github.com/apachecn/scikit-learn-doc-zh) 2. [pytorch 0.3 中文文档](https://github.com/apachecn/pytorch-doc-zh) 3. [TensorFlow R1.2 中文文档](http://cwiki.apachecn.org/pages/viewpage.action?pageId=10030122) 4. [xgboost 中文文档](https://github.com/apachecn/xgboost-doc-zh) 5. [lightgbm 中文文档](https://github.com/apachecn/lightgbm-doc-zh) 6. [fasttext 中文文档](https://github.com/apachecn/fasttext-doc-zh) 7. [gensim 中文文档](https://github.com/apachecn/gensim-doc-zh)