The contents include : Foreword, Setting Up a Python
Programming Environment, An Introduction to Machine Learning, How To Build a
Machine Learning Classifier in Python with Scikit-learn, How To Build a Neural
Network to Recognize Handwritten Digits with TensorFlow, Bias-Variance for Deep
Reinforcement Learning: How To Build a Bot for Atari with OpenAI Gym.
Author(s): Lisa Tagliaferri, Michelle Morales, Ellie
Birbeck, and Alvin Wan
teaches the basics of programming in Python, which is an industrial-strength
programming language used at companies like Google and Industrial Light and
Magic. Topics covered includes: Python basics, Booleans, Strings, Modules,
Loops, Lists, Dictionaries, Files, Classes, Sorting.
explains the following topics: Variables, expressions and statements, Functions,
conditionals and recursion, Fruitful functions and iteration, Strings and lists,
Tuples and dictionaries, Files and exceptions, Classes and objects, Class
methods and composition, Inheritance.
Goal of this note is to teach
the following topics: Python integers, non-decimal integers, Python floats,
precision of floats, Boolean algebra, complex numbers, convert numbers into
different basic data types.
This note covers the following topics: Native Datatypes, Comprehensions,
Strings, Regular Expressions, Installing Python, Closures and Generators,
Classes and Iterators, Advanced Iterators, Unit Testing, Refactoring, Files,
XML, Serializing Python Objects, HTTP Web Services, Case Study: Porting chardet
to Python 3, Packaging Python Libraries, Porting Code to Python 3 with 2to3 and
Special Method Names.