
Author 
Amit Saha 
ISBN10 
9781593276409 
Year 
2015 
Pages 
264 
Language 
en 
Publisher 
No Starch Press 
DOWNLOAD NOW
READ ONLINE
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 quadraticequation 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.

Author 
Amit Saha 
ISBN10 
9781593277192 
Year 
20150801 
Pages 
264 
Language 
en 
Publisher 
No Starch Press 
DOWNLOAD NOW
READ ONLINE
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 quadraticequation 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

Author 
Amit Saha 
ISBN10 
9781593277192 
Year 
20150801 
Pages 
264 
Language 
en 
Publisher 
No Starch Press 
DOWNLOAD NOW
READ ONLINE
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 quadraticequation 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

Author 
Mahesh Venkitachalam 
ISBN10 
9781593277338 
Year 
20151001 
Pages 
352 
Language 
en 
Publisher 
No Starch Press 
DOWNLOAD NOW
READ ONLINE
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 realworld 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 Spirographlike 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.

Author 
J.C. Bautista 
ISBN10 
9781326017965 
Year 
20140913 
Pages 
268 
Language 
en 
Publisher 
Lulu.com 
DOWNLOAD NOW
READ ONLINE
"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.

Author 
Eric Matthes 
ISBN10 
9781593276034 
Year 
20151120 
Pages 
560 
Language 
en 
Publisher 
No Starch Press 
DOWNLOAD NOW
READ ONLINE
Learn Python—Fast! Python Crash Course is a fastpaced, 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 superhandy 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

Author 
John V. Guttag 
ISBN10 
9780262529624 
Year 
20160812 
Pages 
472 
Language 
en 
Publisher 
MIT Press 
DOWNLOAD NOW
READ ONLINE
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.

Author 
Christian Hill 
ISBN10 
9781107075412 
Year 
20160131 
Pages 
482 
Language 
en 
Publisher 
Cambridge University Press 
DOWNLOAD NOW
READ ONLINE
Learn to master basic programming tasks from scratch with reallife scientific examples in this complete introduction to Python.

Author 
Jesse M. Kinder 
ISBN10 
9781400873982 
Year 
20150701 
Pages 
160 
Language 
en 
Publisher 
Princeton University Press 
DOWNLOAD NOW
READ ONLINE
Python is a computer programming language that is rapidly gaining popularity throughout the sciences. 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 opensource 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 threedimensional 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. Webbased resources also accompany this guide and include code samples, data sets, and more.

Author 
Hans Petter Langtangen 
ISBN10 
9783662498873 
Year 
20160728 
Pages 
922 
Language 
en 
Publisher 
Springer 
DOWNLOAD NOW
READ ONLINE
The book serves as a first introduction to computer programming of scientific applications, using the highlevel Python language. The exposition is example and problemoriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlabstyle" and procedural programming as well as objectoriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical onevariable 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 realworld problems using objects and functions and embracing the objectoriented 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
Introduction to the Python computer language for mathematicians and scientists. Topics in scientific computation drawn from statistics, machine learning, mathematics, geometry, and the sciences. Target audience: students with calculus and linear algebra but no previous programming background. Includes over 300 exercises and projects for students.

Author 
Tony Ojeda 
ISBN10 
9781783980253 
Year 
20140925 
Pages 
396 
Language 
en 
Publisher 
Packt Publishing Ltd 
DOWNLOAD NOW
READ ONLINE
If you are an aspiring data scientist who wants to learn data science and numerical programming concepts through handson, realworld project examples, this is the book for you. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of data science projects, the steps in the data science pipeline, and the programming examples presented in this book. Since the book is formatted to walk you through the projects with examples and explanations along the way, no prior programming experience is required.

Author 
Joel Grus 
ISBN10 
9781491904404 
Year 
20150414 
Pages 
330 
Language 
en 
Publisher 
"O'Reilly Media, Inc." 
DOWNLOAD NOW
READ ONLINE
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 knowhow 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 knearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

Author 
Jaan Kiusalaas 
ISBN10 
9781107033856 
Year 
20130121 
Pages 
432 
Language 
en 
Publisher 
Cambridge University Press 
DOWNLOAD NOW
READ ONLINE
Provides an introduction to numerical methods for students in engineering. It uses Python 3, an easytouse, highlevel programming language.

Author 
Hemant Kumar Mehta 
ISBN10 
9781783288830 
Year 
20150923 
Pages 
300 
Language 
en 
Publisher 
Packt Publishing Ltd 
DOWNLOAD NOW
READ ONLINE
A complete guide for Python programmers to master scientific computing using Python APIs and tools About This Book The basics of scientific computing to advanced concepts involving parallel and large scale computation are all covered. Most of the Python APIs and tools used in scientific computing are discussed in detail The concepts are discussed with suitable example programs Who This Book Is For If you are a Python programmer and want to get your hands on scientific computing, this book is for you. The book expects you to have had exposure to various concepts of Python programming. What You Will Learn Fundamentals and components of scientific computing Scientific computing data management Performing numerical computing using NumPy and SciPy Concepts and programming for symbolic computing using SymPy Using the plotting library matplotlib for data visualization Data analysis and visualization using Pandas, matplotlib, and IPython Performing parallel and high performance computing Reallife case studies and best practices of scientific computing In Detail In today's world, along with theoretical and experimental work, scientific computing has become an important part of scientific disciplines. Numerical calculations, simulations and computer modeling in this day and age form the vast majority of both experimental and theoretical papers. In the scientific method, replication and reproducibility are two important contributing factors. A complete and concrete scientific result should be reproducible and replicable. Python is suitable for scientific computing. A large community of users, plenty of help and documentation, a large collection of scientific libraries and environments, great performance, and good support makes Python a great choice for scientific computing. At present Python is among the top choices for developing scientific workflow and the book targets existing Python developers to master this domain using Python. The main things to learn in the book are the concept of scientific workflow, managing scientific workflow data and performing computation on this data using Python. The book discusses NumPy, SciPy, SymPy, matplotlib, Pandas and IPython with several example programs. Style and approach This book follows a handson approach to explain the complex concepts related to scientific computing. It details various APIs using appropriate examples.