【CheatSheets】AI速查表集合 一图胜千言

机器学习和深度学习工程师必备-速查表
机器学习很复杂。对于新手来说，如果他们没有合适的学习资源，则开始学习机器学习会很痛苦。大多数机器学习库很难理解，学习曲线可能会令人沮丧。

最近在Github发现一个仓库，名字为cheatsheets-ai ，https://github.com/kailashahirwar/cheatsheets-ai，其中包含来自不同来源的不同机器学习框架的备忘单。

备忘单列表：

1. Keras
2. Numpy
3. Pandas
4. Scipy
5. Matplotlib
6. Scikit-Learn
7. Neural Networks Zoo
8. ggplot2
9. PySpark
10. R Studio
11. Jupyter Notebook
12. Dask

1. Keras

来源— https://www.datacamp.com/community/blog/keras-cheat-sheet#gs.DRKeNMs

2. Numpy

来源 — https://www.datacamp.com/community/blog/python-numpy-cheat-sheet#gs.AK5ZBgE

3. Pandas

来源- https://www.datacamp.com/community/blog/pandas-cheat-sheet-python#gs.HPFoRIc

4. Scipy

来源 — https://www.datacamp.com/community/blog/python-scipy-cheat-sheet#gs.JDSg3OI

5. Matplotlib

来源 — https://www.datacamp.com/community/blog/python-matplotlib-cheat-sheet#gs.uEKySpY

6. Scikit-learn

来源 — https://www.datacamp.com/community/blog/scikit-learn-cheat-sheet

7. Neural Networks Zoo

来源— http://www.asimovinstitute.org/neural-network-zoo/

8. ggplot2

来源— https://www.rstudio.com/wp-content/uploads/2015/03/ggplot2-cheatsheet.pdf

9. PySpark

来源 — https://www.datacamp.com/community/blog/pyspark-sql-cheat-sheet

10. R Studio (dplyr and tidyr)

来源 — https://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf

11. Jupyter Notebook

来源 — https://www.datacamp.com/community/blog/jupyter-notebook-cheat-sheet

12. Dask

来源— http://docs.dask.org/en/latest/_downloads/daskcheatsheet.pdf