Mathematical & Statistical Software

With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application...

CUDA is now the dominant language used for programming GPUs, one of the most exciting hardware developments of recent decades. With CUDA, you can use a desktop PC for work that would have previously required a large cluster of PCs or access to a HPC...

A start-to-finish guide to one of the most useful programming languages for researchers in a variety of fields In the newly revised Third Edition of The R Book, a team of distinguished teachers and researchers delivers a user-friendly and comprehensive...

The application and interpretation of statistics are central to ecological study and practice. Ecologists are now asking more sophisticated questions than in the past. These new questions, together with the continued growth of computing power and the...

An accessible primer on how to create effective graphics from dataThis book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how...

Now in its second edition, this textbook provides an introduction to Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from...

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...

This book is not available as a print inspection copy. To download an e-version click here or for more information contact your local sales representative. 'Takes the challenging and makes it understandable. The book contains useful advice on the...

Self-driving cars, natural language recognition, and online recommendation engines are all possible thanks to Machine Learning. Now you can create your own genetic algorithms, nature-inspired swarms, Monte Carlo simulations, cellular automata, and...

This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with Python, we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of...

This book provides an undergraduate introduction to analysing data for data science, computer science, and quantitative social science students. It uniquely combines a hands-on approach to data analysis - supported by numerous real data examples and...

The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small,...

Baseball is not the only sport to use "moneyball." American football fans, teams, and gamblers are increasingly using data to gain an edge against the competition. Professional and college teams use data to help select players and identify team needs...

Become a stats superstar by using Excel to reveal the powerful secrets of statistics Microsoft Excel offers numerous possibilities for statistical analysis-and you don't have to be a math wizard to unlock them. In Statistical Analysis with Excel For...

Quantum computers are poised to kick-start a new computing revolution-and you can join in right away. If you're in software engineering, computer graphics, data science, or just an intrigued computerphile, this book provides a hands-on programmer's guide...

An authoritative introduction to the latest comparative methods in evolutionary biologyPhylogenetic comparative methods are a suite of statistical approaches that enable biologists to analyze and better understand the evolutionary tree of life, and shed...

Mathematics is beautiful--and it can be fun and exciting as well as practical. Good Math is your guide to some of the most intriguing topics from two thousand years of mathematics: from Egyptian fractions to Turing machines; from the real meaning of...

Python Programming and Numerical Methods: A Guide for Engineers and Scientists introduces programming tools and numerical methods to engineering and science students, with the goal of helping the students to develop good computational problem-solving...

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...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781944183073Author Stephen WolframPage Count 376Imprint Wolfram Media IncPublisher Wolfram Media IncWeight(grams) 454gDimensions(mm) 254mm * 178mm * 26mm

Candlesticks have become a key component of platforms and charting programs for financial trading. With these charts, traders can learn underlying patterns for interpreting price action history and forecasts. This A-Z guide shows portfolio managers,...

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing...

Master the geometry behind CAD, game engines, GIS, and more! Geometry for Programmers is a hands-on book teaching you the maths behind the tools and libraries to create simulations, 3D prints, and other models in the physical world. Ideal for developers...

This book provides a unique tour of university mathematics with the help of Python. Written in the spirit of mathematical exploration and investigation, the book enables students to utilise Python to enrich their understanding of mathematics through: ...

An Introduction to R and Python for Data Analysis helps teach students to code in both R and Python simultaneously. As both R and Python can be used in similar manners, it is useful and efficient to learn both at the same time, helping lecturers and...

Perform data analysis with R quickly and efficiently with more than 275 practical recipes in this expanded second edition. The R language provides everything you need to do statistical work, but its structure can be difficult to master. These...

Harness the full power of the behavioral data in your company by learning tools specifically designed for behavioral data analysis. Common data science algorithms and predictive analytics tools treat customer behavioral data, such as clicks on a website...

Practice making sense of data with IBM's SPSS Statistics software SPSS Statistics Workbook For Dummies gives you the practice you need to navigate the leading statistical software suite. Data management and analysis, advanced analytics, business...

Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to...

This monograph aims to promote original mathematical methods to determine the invariant measure of two-dimensional random walks in domains with boundaries. Such processes arise in numerous applications and are of interest in several areas of mathematical...

The world's most popular spreadsheet program is now more powerful than ever, but it's also more complex. That's where this Missing Manual comes in. With crystal-clear explanations and hands-on examples, Excel 2013: The Missing Manual shows you how to...

Construct, analyze, and visualize networks with networkx, a Python language module. Network analysis is a powerful tool you can apply to a multitude of datasets and situations. Discover how to work with all kinds of networks, including social, product,...

Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, you'll learn how to use the essential R tools you need to know to analyze...

The quantum computing market is predicted to grow by nearly $1.3 billion over the next five years. Why? Given their quantum mechanical nature, quantum computers are expected to solve difficult problems in chemistry, optimization, finance, and machine...

Learn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide, developers and data scientists will discover how graph analytics deliver...

Think you can't have fun learning statistics? Think again. The Manga Guide to Statistics will teach you everything you need to know about this essential discipline, while entertaining you at the same time. With its unique combination of Japanese-style...

Alan C. Acock's A Gentle Introduction to Stata, Revised Sixth Edition is aimed at new Stata users who want to become proficient in Stata. After reading this introductory text, new users will be able to not only use Stata well but also learn new aspects...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780262035828Author Mike X CohenFormat HardbackPage Count 576Imprint MIT PressPublisher MIT Press LtdDimensions(mm) 229mm * 178mm * 25mm

Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and...

Based on their extensive experience with teaching R and statistics to applied scientists, the authors provide a beginner's guide to R. To avoid the difficulty of teaching R and statistics at the same time, statistical methods are kept to a minimum. The...