Introduction to Python for Computational Science and Engineering
This note covers the following topics: A powerful calculator, Data types and data structures, introspection, Input and output, Control flow, Function and modules, Functional tools, Common tasks, Python shells, Symbolic computation, Numerical Computation, Numerical python arrays, Visualising data, Numerical method using python, Pandas data science with python, Python packages and environments.
Author(s): Hans Fangohr
267 Pages
Lecture notes on python functions
This book explains the following topics: Introduction and Review, variables, Expressions, Operators, For Loops, Range For Loops, Python Functions : Karel functions, function Analogy, Function as python Objects and Variable Scope.
Author(s): NA
116 Pages
Extremely versatile and popular among developers, Python is a good general-purpose language that can be used in a variety of applications. If you use the book in the order it is laid out, you’ll begin your exploration in Python by understanding the key differences between Python 3 and the previous versions of the language. The contents include :Python 2 vs Python 3: Practical Considerations, How To Install Python 3 and Set Up a Local Programming, Environment on Ubuntu 16.04, How To Install Python 3 and Set Up a Local Programming, Environment on macOS, How To Install Python 3 and Set Up a Local Programming, Environment on Windows 10, How To Install Python 3 and Set Up a Local Programming, Environment on CentOS 7, How To Install Python 3 and Set Up a Programming Environment on an Ubuntu 16.04 Server, How To Write Your First Python 3 Program, How To Work with the Python Interactive Console, How To Write Comments, Understanding Data Types, An Introduction to Working with Strings, How To Format Text, String Functions, How To Index and Slice Strings, How To Convert Data Types, Variables, String Formatters, How To Do Math with Operators, Built-in Python 3,Functions for Working with Numbers, Understanding Boolean Logic, Understanding Lists, List Methods, Understanding List Comprehensions, Understanding Tuples, Understanding Dictionaries, How To Import Modules, How To Write Modules, How To Write Conditional Statements, How To Construct While Loops, How To Construct For Loops, How To Use Break, Continue, and Pass Statements when Working with Loops, Construct Classes and Define Objects, Understanding Class and Instance Variables, Understanding Inheritance, How To Apply Polymorphism to Classes, How To Use the Python Debugger, How To Debug Python with an Interactive Console, How To Use Logging, Port Python 2 Code to Python 3.
Author(s): Lisa Tagliaferri, DigitalOcean, New York City, New York, USA
459 Pages
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
Python Programming Course Material
The contents include: Introductions, Operators in Python, Input and Output Statements, Control flow Statements, Strings, Files, Lists, Sets, Tuples, Dictionaries, Functions, Modules.
Author(s): Mr. P. Prathap Naidu
376 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
