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
This note covers the following
topics: Python syntax, Control flow, Functions, Odds and ends,Object-oriented
programming, Exception handling,Type checking, Exception handling, main
differences between Python 2.x and Python 3.x, Recursion, Functional
programming, Command-line arguments, Generator.
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.
assumes that you know no Python whatsoever. This note covers Python 2.2 to 2.6, which
are the most common versions currently in useľ it does NOT cover the recently released Python 3.0 (or 3.1) since those
versions of Python are so new.
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.
This reference manual describes the syntax and core
semantics of the Python language. Topics covered includes: Lexical analysis,
Data model, Execution model , Expressions, Simple statements, Compound
statements, Top-level components and Full Grammar specification.