Книги по Machine Learning (ML)

This new volume provides in-depth and detailed knowledge about the latest research in image processing and computer vision techniques. Explaining the machine learning algorithms and models involved, the authors differentiate between the various algorithms available and how to choose which to use for the most precise results for a specific task involving certain constraints. The volume provides rea...

Deep learning made simple.Dip into deep learning without drowning in theory with this fully updated edition of Practical Deep Learning from experienced author and AI expert Ronald T. Kneusel.After a brief review of basic math and coding principles, you’ll dive into hands-on experiments and learn to build working models for everything from image analysis to creative writing, and gain a th...

Master Zig's blend of safety and performance by building real-world systems applications, and learn memory management through to compile-time execution to create reliable software with full control and zero hidden behaviorsKey FeaturesWrite high-performance code with Zig's clear, no-surprises approach to control flowDiscover memory management techniques to get complete control without sacrificing...

Artificial intelligence is redefining how software is created, enabling developers to code faster, improve accuracy, and bring innovative ideas to life. In today’s competitive technology landscape, AI-assisted programming is no longer optional; it’s a core skill for building modern web applications and machine learning solutions.This book systematically guides you through the whole development cyc...

Deep Learning with Python, Third Edition puts the power of deep learning in your hands. This new edition includes the latest Keras and TensorFlow features, generative AI models, and added coverage of PyTorch and JAX. Learn directly from the creator of Keras and step confidently into the world of deep learning with Python.In Deep Learning with Python, Third Edition you’ll discover:De...

Узнайте, что происходит внутри черного ящика! Для использования глубокого обучения вам придется подготовить данные, выбрать правильную модель, обучить ее, оценить качество и точность и предусмотреть обработку неопределенности и изменчивости в выходных данных развернутого решения. Эта книга шаг за шагом знакомит с основными математическими концепциями, которые пригодятся вам как специалисту по данн...

Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, risk analysts, and quantitative and algorithmic analysts will examine Python-based machine learning and deep learning models for assessing financial risk. Building hands-on AI-based financial modeling skills, you'll learn how to r...

Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments...

React Hooks allow you to easily encapsulate, reuse, and refactor logic with the same level of simplicity that components bring to user interface organization.In this second edition, React expert and author of many popular React books, Daniel Bugl guides you through the full spectrum of React Hooks, and teaches you how to handle forms, routing, and data fetching in modern React development. This ed...

Dive into the world of data science with "Data Science with Rust," your comprehensive guide to mastering data analysis and machine learning using Rust’s powerful and type-safe code. Written by Hayden Van Der Post, a seasoned psychologist, method actor, and entrepreneur with a knack for breaking down complex subjects into engaging and understandable content, this book promises to transform the way...

Те, кто знаком с концепциями искусственного интеллекта (ИИ) и машинного обучения (МО), могут возразить, что они наиболее подходят для более мощных вычислительных платформ. Однако недавние разработки позволили использовать определенные приложения на микроконтроллерах после их обучения. В этой книге обсуждаются методы ИИ и МО специально для микроконтроллеров. Цель состоит в том, чтобы познакоми...

In this stimulating journey of Rust, you'll learn how to use the Rust programming language in conjunction with machine learning. It's not a full guide to learning machine learning with Rust. Instead, it's more of a journey that shows you what's possible when you use Rust to solve machine learning problems. Some people like Rust because it is quick and safe. This book shows how those qualities can...

This book is an in-depth guide that merges machine learning techniques with OpenCV, the most popular computer vision library, using Python. The book introduces fundamental concepts in machine learning and computer vision, progressing to practical implementation with OpenCV. Concepts related to image preprocessing, contour and thresholding techniques, motion detection and tracking are explained in...

Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorithms based on machine learning and reinforcement le...

Modern systems contain multi-core CPUs and GPUs that have the potential for parallel computing. But many scientific Python tools were not designed to leverage this parallelism. With this short but thorough resource, data scientists and Python programmers will learn how the Dask open source library for parallel computing provides APIs that make it easy to parallelize PyData libraries including NumP...