This book looks at each stage of the web development process, showing how to combine Rust and modern web development principles to build supercharged web apps.Maxwell Flitton shows how to avoid common pitfalls when migrating from traditional dynamic programming languages. Later chapters explore the Actix Web framework, processing JSON requests, creating RESTful services in Rust and building an automated deployment process for the app on an AWS EC2 instance and Docker Hub.

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This book shows how the Raspberry Pi, Python and Linux drivers can be used for the Internet of Things. Pi OS, the Raspberry Pi’s operating system, is Linux- based and Linux drivers are available for many off-the-shelf IoT devices. This book explains how, so overcoming the lack of documentation to help you get started. Throughout the book you will find a practical approach to understanding electronic circuits and datasheets and translating this to code, specifically using Python. The emphasis is on understanding how things work so that you can apply your new knowledge to your own projects.

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As its subtitle states, this is a Python-Based Introduction which is aimed at developers curious about machine learning but who don't know where to start. Ron Kneusel focuses on the subfield of machine learning known as deep learning and explains core concept to provide the foundation to start building your own models. After an introduction to Python, the author moves through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models’ performance.

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This book is a collection of forty-six classic papers in computer science that map the evolution of the field. Harry R. Lewis has chosen papers that cover all aspects of computer science: theory and practice, architectures and algorithms, and logic and software systems, with an emphasis on the period of 1936-1980 but also including important works from the pre-history of computing. Offering papers by thinkers ranging from Aristotle and Leibniz to Alan Turing and Nobert Wiener, the book documents the discoveries and inventions that created today's digital world.

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This book covers the key design concepts of JavaScript that lead to clean, lean, modular, and easy-to-maintain code. Luis Atencio covers cutting edge APIs, language features, and coding styles to tackle tricky problems in an elegant manner. Along the way, he discusses good object design, how to drive business logic with functional thinking, and untangle complex data flows.

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Power Apps Component Framework is used to extend the capabilities of model-driven and canvas apps. In this book, Danish Naglekar shows the basics as well as advanced topics using practical examples. The book covers different ways of debugging code components and guides you through the process of building code components for datasets. You'll also explore the functions and methods provided by the framework to enhance your controls using powerful sets of libraries and extensions.

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In this book, described as  "A journey of imagination, exploration, and beautiful data visualizations", Nadieh Bremer and Shirley Wu document the creative process behind 24 data visualization projects, and combine this with powerful technical insights which reveal the mindset behind coding creatively. Exploring 12 different themes – from the Olympics to Presidents & Royals and from Movies to Myths & Legends – each pair of visualizations explores different technologies and forms, blurring the boundary between visualization as an exploratory tool and an artform in its own right.

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Worst-case analysis, the cornerstone of most algorithm courses is where an algorithm is assessed by its worst performance on any input of a given size. The purpose of this book is to popularize several alternatives to worst-case analysis and their most notable algorithmic applications, from clustering to linear programming to neural network training. Tim Roughgarden along with forty leading researchers have contributed introductions to different facets of this field, emphasizing the most important models and results, many of which are suitable for beginners to the concepts of computer science and machine learning.

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This illustrated guide to the chaos of the natural world and the mathematics of fractals is aimed at anyone who has ever wanted to understand the patterns in leaves or the creation of snowflakes. Oliver Linton takes a journey into the mathematics of fractals, diving into everything from coastlines to carpets to reveal some of the intriguing patterns in science and nature.

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This book comes complete with a comprehensive overview of the new capabilities of C++20. Author Marc Gregoire explains each feature of the newly updated programming language in detail and with examples. Case studies that include extensive, working code round out the book.

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This book shows how to use Python for data analysis by exploring the different phases and methodologies used in data analysis and showing how to use modern libraries from the Python ecosystem to create efficient data pipelines. Avinash Navlani, Armando Fandango and Ivan Idris start with the essential statistical and data analysis fundamentals using Python. They go on to cover complex data analysis and modeling, data manipulation, data cleaning, and data visualization and also look at how to conduct time series analysis and signal processing using ARMA models.

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This book sets out to explain exactly what machine learning is, how to implement it, and which tools are needed.  John Paul Mueller shows how to build predictive models, detect anomalies, and analyze text and images. Unlike most machine learning books, the fully updated 2nd Edition doesn't assume readers have years of experience using programming languages but covers the entry-level materials that will get you up and running building models you need to perform practical tasks.

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