Free Data Science learning resources.
This is a data science learning path.
1. RECOMMENDED BOOKS IN MY STORE
https://www.amazon.com/shop/pythonprogrammer
2. PYTHON BASICS
Introduction to Python, The Scientific Libraries, Advanced Python Programming and the Pandas
1) Section of Data and Empirics
https://lectures.quantecon.org/py/
2) Chapters 1 - 4 in this book
3. python库
1) Pandas
Pandas tutorial
https://pandas.pydata.org/pandas-docs/stable/getting_started/10min.html
Some excellent pandas code examples
https://github.com/wesm/pydata-book
4.PRACTICE PYTHON PROJECTS
1) MORE PYTHON
- https://github.com/tuvtran/project-based-learning#python
- https://projecteuler.net/
- Work through as many of the examples as you fancy in Chapters 6 and 7 here https://scipython.com/book/
2) DATA EXPLORATION
- https://github.com/StephenElston/ExploringDataWithPython/blob/master/LearningDataVisualization.ipynb
- https://www.kaggle.com/c/titanic#description
4.MATHS
1) LINEAR ALGEBRA 线性代数
- Essence of Linear Algebra https://www.youtube.com/watch?v=fNk_zzaMoSs&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab
- Khan Academy https://www.khanacademy.org/math/linear-algebra
- https://betterexplained.com/articles/linear-algebra-guide
- https://www.math.ubc.ca/~carrell/NB.pdf (Linear Algebra Reference)
- https://math.byu.edu/~klkuttle/EssentialLinearAlgebra.pdf
2)应用数学方法导论Introduction to Methods of Applied Mathematics
https://physics.bgu.ac.il/~gedalin/Teaching/Mater/am.pdf
3) 物理数学工具 Mathematical Tools for Physics
http://www.physics.miami.edu/~nearing/mathmethods/mathematical_methods-one.pdf
4) 微积分学 CALCULUS
- https://youtu.be/WUvTyaaNkzM
- https://www.khanacademy.org/math/calculus-1
- https://www.khanacademy.org/math/calculus-2
- https://www.khanacademy.org/math/multivariable-calculus
5. 概率和统计 PROBABILITY AND STATISTICS
- https://www.khanacademy.org/math/statistics-probability
- http://greenteapress.com/thinkstats/thinkstats.pdf
- https://bookboon.com/en/applied-statistics-ebook
- http://www.wzchen.com/probability-cheatsheet/
1) 统计学习 STATISTICAL LEARNING
- An Introduction to Statistical Learning http://faculty.marshall.usc.edu/gareth-james/ (Essential)
- https://work.caltech.edu/telecourse.html
- Elements of Statistical Learning (Extremely useful) https://web.stanford.edu/~hastie/ElemStatLearn/
6. PYTHON AND DATA SCIENCE
- Chapter 5 Python Data Science Handbook https://github.com/jakevdp/PythonDataScienceHandbook/blob/8a34a4f653bdbdc01415a94dc20d4e9b97438965/notebooks/Index.ipynb
- https://scikit-learn.org/stable/tutorial/index.html
7. DATA STRUCTURES AND ALGORITHMS IN PYTHON
- https://www.udacity.com/course/data-structures-and-algorithms-in-python–ud513
- https://runestone.academy/runestone/books/published/pythonds/index.html
7. TENSORFLOW 机器学习速成课程
8. SQL
8. GIT AND VERSION CONTROL
TAKE THIS CLASS
补充材料 SUPPLEMENTARY MATERIAL
- The Python Tutorial https://docs.python.org/3/tutorial/index.html
- https://www.reddit.com/r/Python/
- https://stackoverflow.com/questions/tagged/python
- https://www.reddit.com/r/datascience/
- https://datascience.stackexchange.com/
- https://jupyter.org/
- How to think like a computer scientist Learning with Python 3 (RLE) http://www.openbookproject.net/thinkcs/python/english3e/
- WRITE A BLOG - https://onextrapixel.com/start-jekyll-blog-github-pages-free/
- SLACK GROUPS:
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