This book is a pragmatic, hands-on guide to creating server-based web applications with Rust. Bastian Gruber shows how to work efficiently using pure Rust, along with important Rust libraries such as tokio for async runtimes, warp for web servers and APIs, and reqwest to run external HTTP requests.

<ASIN:1617299006>

This book provides readers with a single-source reference to static-single assignment (SSA)-based compiler design. It is the first (and up to now only) book that covers in a deep and comprehensive way how an optimizing compiler can be designed using the SSA form. Edited by Fabrice Rastello and Florent Bouchez Tichadou the book has 24 chapters written by 31 authors and has been 12 years in the making.

<ASIN:303080514X>

In recent years the development of new classification and regression algorithms based on deep learning has led to a revolution in the fields of artificial intelligence, machine learning, and data analysis. In this book, Philipp Grohs and Gitta Kutyniok present the current mathematical understanding of deep learning methods from the point of view of the leading experts in the field.

<ASIN:1316516784>

This book, subtitled "An Introduction to Using Anaconda, JupyterLab, and Python's Scientific Libraries", provides an introduction to Python and its most popular tools for scientists and engineers for research, simulations, and collaboration. Lee Vaughan introduces tools including Anaconda, Spyder, Jupyter Notebooks, JupyterLab, and numerous Python libraries.

<ASIN:1718502664>

This book offers one guide packed with seven books explaining programming across multiple languages.  Wallace Wang covers all the principles of programming, algorithms, data structures, debugging programs, and unique applications of programming while looking at some of the most popular programming languages used today.

<ASIN:1119884403>

This is the first book in a three-part series that traces the development of the GPU. In this volume titled "Steps to Invention", Dr. Jon Peddie traces the initial development of the GPU for games, and explores GPU concepts.

<ASIN:3031109678>

This set of textbooks targets novice learners aspiring to acquire advanced knowledge of the topic of data structures and algorithms. and the material has been split across three volumes to help readers in their progression from novice to expert. Throughout the series G A Vijayalakshmi Pai details concepts, techniques and applications pertaining to data structures and algorithms, independent of any programming language.

<ASIN:1786308924>

Subtitled "Using Python, Flask, FastAPI, OpenAPI and more", this book teaches practical techniques for designing robust microservices with APIs that are easy to understand, consume, and maintain. José Haro Peralta draws on his years of experience experimenting with microservices architecture, dodging pitfalls and learning from mistakes he's made.

<ASIN:1617298417>

In this book Robin Wilson focuses on the development of graph theory in North America from 1876 to 1976, from the point at which James Joseph Sylvester took up his appointment as the first professor of mathematics at the Johns Hopkins University to the solution of the longstanding four color problem in 1976 by Kenneth Appel and Wolfgang Haken of the University of Illinois.

<ASIN:0691194025>

This book starts off by showing how to build a simple app using Spring Boot, and then shows how to secure, test, bundle, and deploy it to production. Greg L. Turnquist then looks at how to go "native" and release using GraalVM. Later chapters explore reactive programming and get a taste of scalable web controllers and data operations. The book goes into detail about GraalVM native images and deployment, showing how to secure an application using both routes and method-based rules.

<ASIN:1803233303>

This book sets out to teach the R skills needed to become a data analyst. Scott McCoy starts with just the parts of the R language relevant to data analysis before moving on to hen,the use of R with the tidyverse package to get, clean, prepare, analyze, and visualize data at a professional level. By the end of the book readers will be creating linear regression models and classification models and using them to make predictions. This book contains three realistic analyses that use real-world data.

<ASIN:B0BJXF7F23>

This thoroughly revised second edition of the book introduces the new features and functionality added to the most recent versions of Mathematica using real-world examples and discusses new topics related to machine learning, big data, finance economics, and physics. As suggested by the subtitle "The Wolfram Language in the Real World", José Guillermo Sánchez León introduces examples that strike a balance between relevance and difficulty in terms of Mathematica syntax, allowing readers to incrementally build up their Mathematica skills as they go through the chapters.

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