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We have two series of resources here: Python, Data, and You; and PurePy. Absolute beginners should start with either the [BASICS] section of PD&Y if you want to fast-track to data-driven applications, or from the beginning of PurePy if you're more interested in general programming concepts. Both series combine written resources, worked example videos, and a sprinkling of exercises and challenges.
Although github has a Jupyter notebook viewer, it's not great. They are not interactive. Moreover, the YouTube videos don't display, similarly some of the text formatting doesn't quite work. We recommend downloading this github repo using the button at the top right and viewing them in Juypter Notebook (installed with Anaconda) locally.
Python is one of the strongest and simplest tools for data processing around today, used by thousands of people to build models and perform statistical analysis. In these guides, we will start by looking at the basic tools for data manipulation in Python, then move on to statistical analysis and building more complex models using machine learning algorithms. By the end of reading these guides, you should be comfortable learning about neural networks, natural language processing, or artificial intelligence.
This series exposes the basic concepts of Python programming, including functions, data structures, and eventually classes, giving you the tools you need to structure larger projects, improve your coding skills, and better understand how Python works. The approach is informal, prefering intuition over technicalities. Chapter 0 includes a crash course on command-line computing, a skill that is often taken for granted in other introductory guides.
- Video for PurePy 6 (coming this weekend)
- Video for PurePy 11
- Some PurePy on network and internet
- Extend PurePy 6 to include Regular expressions
- PurePy on utility scripting