Machine Learning

This modern and self-contained book offers a clear and accessible introduction to the important topic of machine learning with neural networks. In addition to describing the mathematical principles of the topic, and its historical evolution, strong...

A guide for using computational text analysis to learn about the social world From social media posts and text messages to digital government documents and archives, researchers are bombarded with a deluge of text reflecting the social world. This...

This comprehensive guide to Android malware introduces current threats facing the world's most widely used operating system. After exploring the history of attacks seen in the wild since the time Android first launched, including several malware families...

Optimise the performance of your systems with practical experiments used by engineers in the world's most competitive industries. Experimentation for Engineers: From A/B testing to Bayesian optimization is a toolbox of techniques for evaluating new...

In the rapidly evolving field of artificial intelligence, this book serves as a crucial resource for understanding the mathematical foundations of AI. It explores the intricate world of tensors, the fundamental elements powering today's advanced deep...

Decision intelligence (DI) has been widely named as a top technology trend for several years, and the Gartner Group reports that more than a third of large organizations are adopting it. Some even say that DI is the next step in the evolution of AI. Many...

Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion,...

The aim of this textbook is to provide undergraduate students with an introduction to the basic theoretical models of computability, and to develop some of the model's rich and varied structure. Students who have already some experience with elementary...

A much-needed guide to implementing new technology in workspaces From experts in the field comes Machine Learning Upgrade: A Data Scientist's Guide to MLOps, LLMs, and ML Infrastructure, a book that provides data scientists and managers with best...

'The advent of machine learning-based AI systems demands that our industry does not just share toys, but builds a new sandbox in which to play with them.' - Phil Bernstein The profession is changing. A new era is rapidly approaching when computers...

ONE OF THE SUNDAY TIMES' BUSINESS BOOKS OF THE YEAR Technology is putting our humanity at risk to an unprecedented degree. This book is not for engineers who write the code or the policy makers who claim they can regulate it. This is a book for you...

Security has become a 'big data' problem. The growth rate of malware has accelerated to tens of millions of new files per year while our networks generate an ever-larger flood of security-relevant data each day. In order to defend against these advanced...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780967987446Author Peter J ScottFormat PaperbackPage Count 356Imprint Nitrosyncretic PressPublisher Nitrosyncretic PressWeight(grams) 476gDimensions(mm)...

Machine Learning for Kids introduces young readers to the concept of Artificial Intelligence (AI) and the related applications of Machine Learning. Readers learn how to create intelligent games like a rock-paper-scissors game that can learn hand motions...

From finance to artificial intelligence, genetic algorithms are a powerful tool with a wide array of applications. But you don't need an exotic new language or framework to get started; you can learn about genetic algorithms in a language you're already...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780262549424Author Marjorie McshaneFormat PaperbackPage Count 350Imprint MIT PressPublisher MIT Press Ltd

Large language models (LLMs) are not just shaping the trajectory of AI, they're also unveiling a new era of security challenges. This practical book takes you straight to the heart of these threats. Author Steve Wilson, chief product officer at Exabeam,...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780262038485Author Robin R. MurphyFormat HardbackPage Count 648Imprint MIT PressPublisher MIT Press LtdDimensions(mm) 229mm * 203mm * 33mm

Go on the complete R journey from tidying your data, whether small, complex, or big, to implementing and evaluating a variety of machine learning models Key Features * The 10th Anniversary Edition of the bestselling R machine learning book, updated with...

Companies are spending billions on machine learning projects, but it's money wasted if the models can't be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning...

An authoritative, up-to-date graduate textbook on machine learning that highlights its historical context and societal impactsPatterns, Predictions, and Actions introduces graduate students to the essentials of machine learning while offering invaluable...

'A penetrating portrait of one of the most significant companies in the world' Ronan Farrow, author of Catch and Kill'With the skill of an award-winning journalist, Horwitz details the inner workings of the tech giant and their outcomes...A must-read.'...

More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom...

Implementing and designing systems that make suggestions to users are among the most popular and essential machine learning applications available. Whether you want customers to find the most appealing items at your online store, videos to enrich and...

Design systems optimized for deep learning models. Written for software engineers, this book teaches you how to implement a maintainable platform for developing deep learning models. In Engineering Deep Learning Systems you will learn how...

Is a computer simulation of a brain sufficient to make it intelligent? Do you need consciousness to have intelligence? Do you need to be alive to have consciousness? This book has a dual purpose. First, it provides a multi-disciplinary research survey...

Machine learning (ML) is progressively reshaping the fields of quantitative finance and algorithmic trading. ML tools are increasingly adopted by hedge funds and asset managers, notably for alpha signal generation and stocks selection. The technicality...

Build predictive models from time-based patterns in your data. Master statistical models including new deep learning approaches for time series forecasting. In Time Series Forecasting in Python you will learn how to: Recognize a...

Edge AI is transforming the way computers interact with the real world, allowing IoT devices to make decisions using the 99% of sensor data that was previously discarded due to cost, bandwidth, or power limitations. With techniques like embedded machine...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780262047326Author Peter CottonFormat HardbackPage Count 216Imprint MIT PressPublisher MIT Press Ltd

Deep Learning for Complete Beginners: A Python-Based Introduction is for complete beginners in machine learning. It introduces fundamental concepts such as classes and labels, building a dataset, and what a model is and does before presenting classic...

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate...

Gain the valuable skills and techniques you need to accelerate the delivery of machine learning solutions. With this practical guide, data scientists and ML engineers will learn how to bridge the gap between data science and Lean software delivery in a...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9780262048613Author Solon BarocasFormat HardbackPage Count 320Imprint MIT PressPublisher MIT Press Ltd

Given the demand for AI and the ubiquity of JavaScript, TensorFlow.js was inevitable. With this Google framework, seasoned AI veterans and web developers alike can help propel the future of AI-driven websites. In this guide, author Gant Laborde--Google...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781734467505Author Nick PsarisFormat PaperbackPage Count 416Imprint Vector SIGMAPublisher Vector SIGMAWeight(grams) 712gDimensions(mm) 235mm * 191mm * 22mm

With demand for scaling, real-time access, and other capabilities, businesses need to consider building operational machine learning pipelines. This practical guide helps your company bring data science to life for different real-world MLOps scenarios...

Elevate your machine learning skills using the Conformal Prediction framework for uncertainty quantification. Dive into unique strategies, overcome real-world challenges, and become confident and precise with forecasting. Key Features Master...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781913666521Author Oliver TheobaldFormat PaperbackPage Count 194Imprint Scatterplot PressPublisher Scatterplot PressWeight(grams) 290gDimensions(mm) 229mm *...

Turning text into valuable information is essential for businesses looking to gain a competitive advantage. With recent improvements in natural language processing (NLP), users now have many options for solving complex challenges. But it's not always...