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从零基础开始机器学习之旅

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。

资料主要包括:

  • 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

cheat sheet

ML

machine learning cheat sheet

numpy

numpy cheat sheet

numpy

pandas

pandas cheat sheet

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

scikit learn

scikit cheat sheet

charts

pyecharts

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

python module lib whl