Python Machine Learning Projects
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
135 Pages
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.
Author(s): Mike Vanier
NA Pages
Introduction to Programming through Python and C
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.
Author(s): Goutam Biswas
121 Pages
A Gentle Introduction to Programming Using Python
This note will provide a gentle introduction to programming using Python for highly motivated students with little or no prior experience in programming computers. Topics covered includes: Variables and types, Functions, basic recursion, Control flow: Branching and repetition, Introduction to objects: Strings and lists, Structuring larger programs, Python modules, debugging programs, Introduction to data structures: Dictionaries, Functions as a type, anonymous functions and list comprehensions.
Author(s): Mihir Kedia and Aseem Kishore
NA Pages
The Python Tutorial by Madhavan Mukund
Python is an easy to learn, powerful programming language. This tutorial does not attempt to be comprehensive and cover every single feature, or even every commonly used feature.
Author(s): Madhavan Mukund
NA Pages
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.
Author(s): Mark Pilgrim
NA Pages
Learning to Program in Python (Alan Gauld)
Currently this section contains no detailed description for the page, will update this page soon.
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Currently this section contains no detailed description for the page, will update this page soon.
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