Want to get started with machine learning in Python? I'll discuss the pros and cons of the scikit-learn library, show how to install my preferred Python distribution, and demonstrate the basic functionality of the Jupyter Notebook. If you don't yet know any Python, I'll also provide four recommended resources for learning Python.

Download the notebook: https://github.com/justmarkham/scikit-learn-videos
Six reasons why I recommend scikit-learn: http://radar.oreilly.com/2013/12/six-reasons-why-i-recommend-scikit-learn.html
API design for machine learning software: http://arxiv.org/pdf/1309.0238v1.pdf
Should you teach Python or R for data science?: https://www.dataschool.io/python-or-r-for-data-science/
scikit-learn installation: http://scikit-learn.org/stable/install.html
Anaconda installation: https://www.anaconda.com/download/
Jupyter installation: https://jupyter.readthedocs.io/en/latest/install.html
nbviewer: http://nbviewer.jupyter.org/
IPython documentation: http://ipython.readthedocs.io/en/stable/
Jupyter Notebook quickstart: http://jupyter.readthedocs.io/en/latest/content-quickstart.html
GitHub's Mastering Markdown: https://guides.github.com/features/mastering-markdown/
Codecademy's Python course: https://www.codecademy.com/learn/learn-python
DataQuest: https://www.dataquest.io/
Google's Python class: https://developers.google.com/edu/python/
Python for Informatics: https://www.py4e.com/

WANT TO GET BETTER AT MACHINE LEARNING? HERE ARE YOUR NEXT STEPS:

1) WATCH my scikit-learn video series:
https://www.youtube.com/playlist?list=PL5-da3qGB5ICeMbQuqbbCOQWcS6OYBr5A

2) SUBSCRIBE for more videos:
https://www.youtube.com/dataschool?sub_confirmation=1

3) JOIN "Data School Insiders" to access bonus content:
https://www.patreon.com/dataschool

4) ENROLL in my Machine Learning course:
https://www.dataschool.io/learn/

5) LET'S CONNECT!
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