该工程主要包含机器学习学习过程中收集的相关资料和实践代码。
- Machine Learning Glossary---This glossary defines general machine learning terms as well as terms specific to TensorFlow.
- awesome-machine-learning-on-source-code---Interesting links & research papers related to Machine Learning applied to source code
- state-of-the-art-result-for-machine-learning-problems---This repository provides state of the art (SoTA) results for all machine learning problems.
- awesome
- 时间序列数据分析
- 自然语言处理NLP
- 基本机器学习算法相关资料
- 深度学习相关资料
- tensorflow相关资料
- kaggle相关资料
- jupyter相关资料
- MachinLearningOnSpark
- 实践代码
实操 | 内存占用减少高达90%,还不用升级硬件?没错,这篇文章教你妙用Pandas轻松处理大规模数据
代码
实践代码主要基于python 3.6.1
,依赖的module有:
- numpy+mkl(最好使用whl安装)
- scipy(最好使用whl安装)
- pandas
- matplotlib & seaborn
- ipython
- jupyter
whl url