Table of Contents

Introduction:

• Organization
• Schedule
• General information

Tools and methods:

• Package management
• Coding environment
• Python basics
• Profiling
• Testing
• Useful modules
• Type hinting
• Collaborating
• Documenting

Algorithmic:

• Complexity
• Recursion
• Divide and Conquer
• Dynamic Programming
• Graphs

Artificial intelligence

• State models
• Reinforcement Learning
• Forward Neural Network

Projects

• Projects

References

[Het14]

Magnus Lie Hetland. Python algorithms : mastering basic algorithms in the python language. Apress, second edition, 2014. URL: https://github.com/0bprashanthc/algorithm-books/blob/master/Python%20Algorithms%20-%20Mastering%20Basic%20Algorithms%20in%20the%20Python%20Language%20-%20Second%20Edition.pdf.

[LS]

Percy Liang and Dorsa Sadigh. Stanford cs221: learn ai (autumn 2019). URL: https://www.youtube.com/playlist?list=PLoROMvodv4rO1NB9TD4iUZ3qghGEGtqNX.

[San]

Grant Sanderson. 3blue1brown: neural networks. URL: https://www.3blue1brown.com/?topic=neural-networks.

[SB18]

Richard S. Sutton and Andrew G. Barto. Reinforcement Learning: An Introduction. The MIT Press, second edition, 2018. URL: http://incompleteideas.net/book/the-book-2nd.html.

Indices and tables

• Index

• Module Index

• Search Page