## Doing Math with Python

*Use Programming to Explore Algebra, Statistics, Calculus, and More!*

**Author**: Amit Saha

**Publisher:**No Starch Press

**ISBN:**1593276400

**Category:**Computers

**Page:**264

**View:**4922

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Doing Math with Python shows you how to use Python to delve into high school–level math topics like statistics, geometry, probability, and calculus. You’ll start with simple projects, like a factoring program and a quadratic-equation solver, and then create more complex projects once you’ve gotten the hang of things. Along the way, you’ll discover new ways to explore math and gain valuable programming skills that you’ll use throughout your study of math and computer science. Learn how to: -Describe your data with statistics, and visualize it with line graphs, bar charts, and scatter plots -Explore set theory and probability with programs for coin flips, dicing, and other games of chance -Solve algebra problems using Python’s symbolic math functions -Draw geometric shapes and explore fractals like the Barnsley fern, the Sierpinski triangle, and the Mandelbrot set -Write programs to find derivatives and integrate functions Creative coding challenges and applied examples help you see how you can put your new math and coding skills into practice. You’ll write an inequality solver, plot gravity’s effect on how far a bullet will travel, shuffle a deck of cards, estimate the area of a circle by throwing 100,000 “darts” at a board, explore the relationship between the Fibonacci sequence and the golden ratio, and more. Whether you’re interested in math but have yet to dip into programming or you’re a teacher looking to bring programming into the classroom, you’ll find that Python makes programming easy and practical. Let Python handle the grunt work while you focus on the math.

## Doing Math with Python

*Use Programming to Explore Algebra, Statistics, Calculus, and More!*

**Author**: Amit Saha

**Publisher:**No Starch Press

**ISBN:**1593277199

**Category:**Computers

**Page:**264

**View:**5511

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Doing Math with Python shows you how to use Python to delve into high school–level math topics like statistics, geometry, probability, and calculus. You’ll start with simple projects, like a factoring program and a quadratic-equation solver, and then create more complex projects once you’ve gotten the hang of things. Along the way, you’ll discover new ways to explore math and gain valuable programming skills that you’ll use throughout your study of math and computer science. Learn how to: –Describe your data with statistics, and visualize it with line graphs, bar charts, and scatter plots –Explore set theory and probability with programs for coin flips, dicing, and other games of chance –Solve algebra problems using Python’s symbolic math functions –Draw geometric shapes and explore fractals like the Barnsley fern, the Sierpinski triangle, and the Mandelbrot set –Write programs to find derivatives and integrate functions Creative coding challenges and applied examples help you see how you can put your new math and coding skills into practice. You’ll write an inequality solver, plot gravity’s effect on how far a bullet will travel, shuffle a deck of cards, estimate the area of a circle by throwing 100,000 "darts" at a board, explore the relationship between the Fibonacci sequence and the golden ratio, and more. Whether you’re interested in math but have yet to dip into programming or you’re a teacher looking to bring programming into the classroom, you’ll find that Python makes programming easy and practical. Let Python handle the grunt work while you focus on the math. Uses Python 3

## Python Playground

*Geeky Projects for the Curious Programmer*

**Author**: Mahesh Venkitachalam

**Publisher:**No Starch Press

**ISBN:**1593277334

**Category:**Computers

**Page:**352

**View:**3411

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Python is a powerful programming language that’s easy to learn and fun to play with. But once you’ve gotten a handle on the basics, what do you do next? Python Playground is a collection of imaginative programming projects that will inspire you to use Python to make art and music, build simulations of real-world phenomena, and interact with hardware like the Arduino and Raspberry Pi. You’ll learn to use common Python tools and libraries like numpy, matplotlib, and pygame to do things like: –Generate Spirograph-like patterns using parametric equations and the turtle module –Create music on your computer by simulating frequency overtones –Translate graphical images into ASCII art –Write an autostereogram program that produces 3D images hidden beneath random patterns –Make realistic animations with OpenGL shaders by exploring particle systems, transparency, and billboarding techniques –Construct 3D visualizations using data from CT and MRI scans –Build a laser show that responds to music by hooking up your computer to an Arduino Programming shouldn’t be a chore. Have some solid, geeky fun with Python Playground. The projects in this book are compatible with both Python 2 and 3.

## Mathematics and Python Programming

**Author**: J.C. Bautista

**Publisher:**Lulu.com

**ISBN:**1326017969

**Category:**Technology & Engineering

**Page:**268

**View:**4642

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"We have developed 120 Python programs and more than 110 illustrations in a work that will be useful both to students of science of the first university science courses, as well as high school students and teachers, and to anyone interested in Python programming intending to acquire new tools to expose mathematical concepts in a didactic and modern fashion....The book begins with a detailed introduction to Python, followed by ten chapters of mathematics with its corresponding Python programs, results and graphs."--Cover.

## Python for Kids

*A Playful Introduction to Programming*

**Author**: Jason R. Briggs

**Publisher:**No Starch Press

**ISBN:**1593274076

**Category:**Juvenile Nonfiction

**Page:**344

**View:**6085

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Introduces the basics of the Python programming language, covering how to use data structures, organize and reuse code, draw shapes and patterns with turtle, and create games and animations with tkinter.

## Learning Scientific Programming with Python

**Author**: Christian Hill

**Publisher:**Cambridge University Press

**ISBN:**1107075416

**Category:**Computers

**Page:**482

**View:**8248

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Learn to master basic programming tasks from scratch with real-life scientific examples in this complete introduction to Python.

## WRITE YOUR FIRST PROGRAM

**Author**: AMIT SAHA

**Publisher:**PHI Learning Pvt. Ltd.

**ISBN:**8120347412

**Category:**Computers

**Page:**242

**View:**400

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This introductory book on programming introduces computer programming using C and Python programming languages on Microsoft Windows and Linux operating systems to beginners. The book assumes no familiarity with programming and teaches the basics of programming to its readers. It helps the readers to write programs to solve problems in computer science, finance, mathematics and physics. Unlike other introductory guides to programming, Write Your First Program focuses on the exact information that beginners are required to apply while creating practical programs. The book is organized in eight chapters–with each chapter introducing a major programming topic, focusing on the concepts and then implementing them in both the languages. This book will teach you to write your first program and progress on to concepts such as working with data, decision making, persistent data storage and implementing mathematical operations. Apart from programming, the book also discusses version control systems and open source projects. The aim of the book is to focus on the programming logic, and then see how the logic can be implemented using two different languages. Thus, it helps the readers to learn two vastly different ways of programming. This book is intended for all those who are interested to learn/sharpen their programming skills. Companion Website The website for this book (www.phindia.com/saha) is an integral part of the book where you will find: • Extended treatment of certain topics • Additional tips and tutorials • Questions and comments page

## Hacking Math Class with Python

*Exploring Math Through Computer Programming*

**Author**: Peter A. Farrell

**Publisher:**Createspace Independent Publishing Platform

**ISBN:**9781508656944

**Category:**

**Page:**144

**View:**7910

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A new kind of math book! Explore math topics from arithmetic to calculus by creating your own graphing and solving tools using Python. Create 2D and 3D graphics, harmonograph and spirograph designs, and fractals in this interactive and visual exploration of mathematics. "A great resource to play with Math and Python via the turtle module, solving equations numerically and 3D graphics via Pi3D." - Amit Saha, author of Doing Math With Python Imagine learning math and Python programming at the same time! You'll learn to use loops, variables, functions, conditionals and lists and apply them to all your math problems. No previous computer experience is required.

## Cracking Codes with Python

*An Introduction to Building and Breaking Ciphers*

**Author**: Al Sweigart

**Publisher:**No Starch Press

**ISBN:**1593278691

**Category:**Computers

**Page:**416

**View:**5355

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Learn how to program in Python while making and breaking ciphers—algorithms used to create and send secret messages! After a crash course in Python programming basics, you’ll learn to make, test, and hack programs that encrypt text with classical ciphers like the transposition cipher and Vigenère cipher. You’ll begin with simple programs for the reverse and Caesar ciphers and then work your way up to public key cryptography, the type of encryption used to secure today’s online transactions, including digital signatures, email, and Bitcoin. Each program includes the full code and a line-by-line explanation of how things work. By the end of the book, you’ll have learned how to code in Python and you’ll have the clever programs to prove it! You’ll also learn how to: - Combine loops, variables, and flow control statements into real working programs - Use dictionary files to instantly detect whether decrypted messages are valid English or gibberish - Create test programs to make sure that your code encrypts and decrypts correctly - Code (and hack!) a working example of the affine cipher, which uses modular arithmetic to encrypt a message - Break ciphers with techniques such as brute-force and frequency analysis There’s no better way to learn to code than to play with real programs. Cracking Codes with Python makes the learning fun!

## Mathematics for the Digital Age and Programming in Python

**Author**: Maria Litvin,Gary Litvin

**Publisher:**Skylight Pub

**ISBN:**9780982477540

**Category:**Computers

**Page:**337

**View:**7871

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Never HIGHLIGHT a Book Again Includes all testable terms, concepts, persons, places, and events. Cram101 Just the FACTS101 studyguides gives all of the outlines, highlights, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanies: 9780982477540. This item is printed on demand.

## Introduction to Computation and Programming Using Python

*With Application to Understanding Data*

**Author**: John V. Guttag

**Publisher:**MIT Press

**ISBN:**0262529629

**Category:**Computers

**Page:**472

**View:**2148

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The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization.

## Python 3

*Pocket Primer*

**Author**: James R. Parker

**Publisher:**Stylus Publishing, LLC

**ISBN:**1683920872

**Category:**Computers

**Page:**250

**View:**6527

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As part of the best selling Pocket Primer series, this book is an effort to give programmers sufficient knowledge of Python 3 to be able to work on their own projects. Although it covers all of the basic concepts, the book features a chapter on PyGame, which allows a programmer to handle graphics, mouse and keyboard interaction, and play sounds and videos. The demonstration example for that chapter is a Lunar Lander game. Another feature is the chapter on communication, which makes use of one of Python’s best features: a collection of modules for sending and receiving Email, communicating between computers, and working with Twitter and Web pages. Companion files that accompany this book contain all of the code examples as complete working programs. This means that there is no need to key them in, so they can be executed and perhaps modified or expanded. Features: •Features a chapter on PyGame, which allows a programmer to handle graphics, mouse / keyboard interaction, and play sounds and videos •Explores communication in depth, making use of one of Python’s best features: a collection of modules for sending and receiving Email, communicating between computers, and working with Twitter and Web pages. •Companion files contain all of the code examples as complete working programs On the Companion Files: (also available from the publisher for downloading) •Source code samples •All images from the text (including 4-color)

## Python Crash Course

*A Hands-On, Project-Based Introduction to Programming*

**Author**: Eric Matthes

**Publisher:**No Starch Press

**ISBN:**1593277393

**Category:**Computers

**Page:**560

**View:**5572

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Python Crash Course is a fast-paced, thorough introduction to Python that will have you writing programs, solving problems, and making things that work in no time. In the first half of the book, you’ll learn about basic programming concepts, such as lists, dictionaries, classes, and loops, and practice writing clean and readable code with exercises for each topic. You’ll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you’ll put your new knowledge into practice with three substantial projects: a Space Invaders–inspired arcade game, data visualizations with Python’s super-handy libraries, and a simple web app you can deploy online. As you work through Python Crash Course you’ll learn how to: –Use powerful Python libraries and tools, including matplotlib, NumPy, and Pygal –Make 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progresses –Work with data to generate interactive visualizations –Create and customize Web apps and deploy them safely online –Deal with mistakes and errors so you can solve your own programming problems If you’ve been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code! Uses Python 2 and 3

## Mazes for Programmers

*Code Your Own Twisty Little Passages*

**Author**: Jamis Buck

**Publisher:**Pragmatic Bookshelf

**ISBN:**1680503960

**Category:**Computers

**Page:**286

**View:**5948

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Unlock the secrets to creating random mazes! Whether you're a game developer, an algorithm connoisseur, or simply in search of a new puzzle, you're about to level up. Learn algorithms to randomly generate mazes in a variety of shapes, sizes, and dimensions. Bend them into Moebius strips, fold them into cubes, and wrap them around spheres. Stretch them into other dimensions, squeeze them into arbitrary outlines, and tile them in a dizzying variety of ways. From twelve little algorithms, you'll discover a vast reservoir of ideas and inspiration. From video games to movies, mazes are ubiquitous. Explore a dozen algorithms for generating these puzzles randomly, from Binary Tree to Eller's, each copiously illustrated and accompanied by working implementations in Ruby. You'll learn their pros and cons, and how to choose the right one for the job. You'll start by learning six maze algorithms and transition from making mazes on paper to writing programs that generate and draw them. You'll be introduced to Dijkstra's algorithm and see how it can help solve, analyze, and visualize mazes. Part 2 shows you how to constrain your mazes to different shapes and outlines, such as text, circles, hex and triangle grids, and more. You'll learn techniques for culling dead-ends, and for making your passages weave over and under each other. Part 3 looks at six more algorithms, taking it all to the next level. You'll learn how to build your mazes in multiple dimensions, and even on curved surfaces. Through it all, you'll discover yourself brimming with ideas, the best medicine for programmer's block, burn-out, and the grayest of days. By the time you're done, you'll be energized and full of maze-related possibilities! What You Need: The example code requires version 2 of the Ruby programming language. Some examples depend on the ChunkyPNG library to generate PNG images, and one chapter uses POV-Ray version 3.7 to render 3D graphics.

## Principles of Data Science

**Author**: Sinan Ozdemir

**Publisher:**Packt Publishing Ltd

**ISBN:**1785888927

**Category:**Computers

**Page:**388

**View:**4334

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Learn the techniques and math you need to start making sense of your data About This Book Enhance your knowledge of coding with data science theory for practical insight into data science and analysis More than just a math class, learn how to perform real-world data science tasks with R and Python Create actionable insights and transform raw data into tangible value Who This Book Is For You should be fairly well acquainted with basic algebra and should feel comfortable reading snippets of R/Python as well as pseudo code. You should have the urge to learn and apply the techniques put forth in this book on either your own data sets or those provided to you. If you have the basic math skills but want to apply them in data science or you have good programming skills but lack math, then this book is for you. What You Will Learn Get to know the five most important steps of data science Use your data intelligently and learn how to handle it with care Bridge the gap between mathematics and programming Learn about probability, calculus, and how to use statistical models to control and clean your data and drive actionable results Build and evaluate baseline machine learning models Explore the most effective metrics to determine the success of your machine learning models Create data visualizations that communicate actionable insights Read and apply machine learning concepts to your problems and make actual predictions In Detail Need to turn your skills at programming into effective data science skills? Principles of Data Science is created to help you join the dots between mathematics, programming, and business analysis. With this book, you'll feel confident about asking—and answering—complex and sophisticated questions of your data to move from abstract and raw statistics to actionable ideas. With a unique approach that bridges the gap between mathematics and computer science, this books takes you through the entire data science pipeline. Beginning with cleaning and preparing data, and effective data mining strategies and techniques, you'll move on to build a comprehensive picture of how every piece of the data science puzzle fits together. Learn the fundamentals of computational mathematics and statistics, as well as some pseudocode being used today by data scientists and analysts. You'll get to grips with machine learning, discover the statistical models that help you take control and navigate even the densest datasets, and find out how to create powerful visualizations that communicate what your data means. Style and approach This is an easy-to-understand and accessible tutorial. It is a step-by-step guide with use cases, examples, and illustrations to get you well-versed with the concepts of data science. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts later on and will help you implement these techniques in the real world.

## A Student's Guide to Python for Physical Modeling

**Author**: Jesse M. Kinder,Philip Nelson

**Publisher:**Princeton University Press

**ISBN:**1400889421

**Category:**Computers

**Page:**168

**View:**5736

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A fully updated tutorial on the basics of the Python programming language for science students Python is a computer programming language that is rapidly gaining popularity throughout the sciences. This fully updated edition of A Student's Guide to Python for Physical Modeling aims to help you, the student, teach yourself enough of the Python programming language to get started with physical modeling. You will learn how to install an open-source Python programming environment and use it to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; and simulation. No prior programming experience is assumed. This tutorial focuses on fundamentals and introduces a wide range of useful techniques, including: Basic Python programming and scripting Numerical arrays Two- and three-dimensional graphics Monte Carlo simulations Numerical methods, including solving ordinary differential equations Image processing Animation Numerous code samples and exercises--with solutions—illustrate new ideas as they are introduced. Web-based resources also accompany this guide and include code samples, data sets, and more. This current edition brings the discussion of the Python language, Spyder development environment, and Anaconda distribution up to date. In addition, a new appendix introduces Jupyter notebooks.

## Data Science from Scratch

*First Principles with Python*

**Author**: Joel Grus

**Publisher:**"O'Reilly Media, Inc."

**ISBN:**1491904402

**Category:**BUSINESS & ECONOMICS

**Page:**330

**View:**1105

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Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

## Mathematical Methods for Physics and Engineering

*A Comprehensive Guide*

**Author**: K. F. Riley,M. P. Hobson,S. J. Bence

**Publisher:**Cambridge University Press

**ISBN:**1139450999

**Category:**Science

**Page:**N.A

**View:**1777

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The third edition of this highly acclaimed undergraduate textbook is suitable for teaching all the mathematics for an undergraduate course in any of the physical sciences. As well as lucid descriptions of all the topics and many worked examples, it contains over 800 exercises. New stand-alone chapters give a systematic account of the 'special functions' of physical science, cover an extended range of practical applications of complex variables, and give an introduction to quantum operators. Further tabulations, of relevance in statistics and numerical integration, have been added. In this edition, half of the exercises are provided with hints and answers and, in a separate manual available to both students and their teachers, complete worked solutions. The remaining exercises have no hints, answers or worked solutions and can be used for unaided homework; full solutions are available to instructors on a password-protected web site, www.cambridge.org/9780521679718.

## A Primer on Scientific Programming with Python

**Author**: Hans Petter Langtangen

**Publisher:**Springer

**ISBN:**3662498871

**Category:**Computers

**Page:**922

**View:**6338

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The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011 This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012 “This fourth edition is a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in Python...” Joan Horvath, Computing Reviews, March 2015