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 explains
the following topics: Types of Digital Computers, Stored Program Computer,
Computer Models, Machine Language Program, Program Execution, Central Processing
Unit, Memory Write, Binary World, Assembly Language Program, High-Level
Languages, Compiler, Operating System, Python Interpreter.
This note covers the
following topics: Basic Principles of Python, String Data, String Operations,
Numeric Data, Types of Numeric Data, Conversion of Scalar Types, Lists, Tuples
and Dictionaries, Input and Output, Programming, Functions, Using Modules,
Writing Modules and Exceptions.
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 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.