The book was written and tested with Python 3.5, though other Python versions (including Python 2.7) should work in nearly all cases.
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages
Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project
A…
It introduces you to many practical skills with the basic tools of ML.
Then go to kaggle.com and try some of the learner competitions. Check out highly upvoted kernels. You'll get exposed to real code running real models, and you'll see for yourself what's popular in the community in terms of libraries and algos
Read
jakevdp / PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
Python Data Science Handbook
This repository contains the entire Python Data Science Handbook, in the form of (free!) Jupyter notebooks.
How to Use this Book
Read the book in its entirety online at jakevdp.github.io/PythonDataScienc...
Run the code using the Jupyter notebooks available in this repository's notebooks directory.
Launch executable versions of these notebooks using Google Colab:
Launch a live notebook server with these notebooks using binder:
Buy the printed book through O'Reilly Media
About
The book was written and tested with Python 3.5, though other Python versions (including Python 2.7) should work in nearly all cases.
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project A…
It introduces you to many practical skills with the basic tools of ML.
Then go to kaggle.com and try some of the learner competitions. Check out highly upvoted kernels. You'll get exposed to real code running real models, and you'll see for yourself what's popular in the community in terms of libraries and algos
OMG I have that. Its about 3 titles down on my reading list. Thank you for sharing those resources, too. If you have any more, please do share!