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Doing Math with Python
Use Programming to Explore Algebra, Statistics, Calculus, and More!
2015
EN
Accessible
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...
Practical Go
Building Scalable Network and Non-Network Applications
2021
EN
YOUR PRACTICAL, HANDS-ON GUIDE TO WRITING APPLICATIONS USING GOGoogle announced the Go programming language to the public in 2009, with the version 1.0 release announced in 2012. Since its announcement to the community, and the compatibility promise of the 1.0 release, the Go language has been used to write scalable and high-impact software programs ranging from command-line applications and critical infrastructure tools to large-scale distributed systems. It’s spe...
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Learning OpenCV
Computer Vision with the OpenCV Library
2008
EN
"This library is useful for practitioners, and is an excellent tool for those entering the field: it is a set of computer vision algorithms that work as advertised."-William T. Freeman, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of TechnologyLearning OpenCV puts you in the middle of the rapidly expanding field of computer vision. Written by the creators of the free open source OpenCV library, this book introduces you to computer vision...
Programming Collective Intelligence
Building Smart Web 2.0 Applications
2008
EN
Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found ...
Data Analysis with Open Source Tools
A Hands-On Guide for Programmers and Data Scientists
2010
EN
Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through...
The Art of R Programming
A Tour of Statistical Software Design
2011
EN
R is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly.The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anon...
R in a Nutshell
A Desktop Quick Reference
2012
EN
If you’re considering R for statistical computing and data visualization, this book provides a quick and practical guide to just about everything you can do with the open source R language and software environment. You’ll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data. Author Joseph Adler illustrates each process with a wealth of examples from medicine, business, and sports.Updated for R 2.14 and 2.15, this second edition includes...
Mathematica Cookbook
Building Blocks for Science, Engineering, Finance, Music, and More
2010
EN
Mathematica Cookbook helps you master the application's core principles by walking you through real-world problems. Ideal for browsing, this book includes recipes for working with numerics, data structures, algebraic equations, calculus, and statistics. You'll also venture into exotic territory with recipes for data visualization using 2D and 3D graphic tools, image processing, and music.Although Mathematica 7 is a highly advanced computational platform, the recipes in thi...
Programming Computer Vision with Python
Tools and algorithms for analyzing images
2012
EN
If you want a basic understanding of computer vision’s underlying theory and algorithms, this hands-on introduction is the ideal place to start. You’ll learn techniques for object recognition, 3D reconstruction, stereo imaging, augmented reality, and other computer vision applications as you follow clear examples written in Python.Programming Computer Vision with Python explains computer vision in broad terms that won’t bog you down in theory. You get complete code samples...
Learning SciPy for Numerical and Scientific Computing Second Edition
Quick solutions to complex numerical problems in physics, applied mathematics, and science with SciPy
2015
EN
Key FeaturesBook DescriptionThis book targets programmers and scientists who have basic Python knowledge and who are keen to perform scientific and numerical computations with SciPy.What you will learnGet to know the benefits of using the combination of Python, NumPy, SciPy, and matplotlib as a programming environment for scientific purposesCreate and manipulate an object array used by SciPyUse SciPy with large matric...
2007
EN
This is the only introduction you'll need to start programming in R, the open-source language that is free to download, and lets you adapt the source code for your own requirements. Co-written by one of the R Core Development Team, and by an established R author, this book comes with real R code that complies with the standards of the language. Unlike other introductory books on the ground-breaking R system, this book emphasizes programming, including the principles that apply to most comp...
2013
EN
The book is written in beginner's guide style with each aspect of NumPy demonstrated with real world examples and required screenshots. If you are a programmer, scientist, or engineer who has basic Python knowledge and would like to be able to do numerical computations with Python, this book is for you. No prior knowledge of NumPy is required.











