Why Machines Learn
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Why Machines Learn
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Author : Anil Ananthaswamy
language : en
Publisher: Penguin Group
Release Date : 2025-08-26
Why Machines Learn written by Anil Ananthaswamy and has been published by Penguin Group this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-26 with Computers categories.
A rich, narrative explanation of the mathematics that has brought us machine learning and the ongoing explosion of artificial intelligence Machine learning systems are making life-altering decisions for us: approving mortgage loans, determining whether a tumor is cancerous, or deciding if someone gets bail. They now influence developments and discoveries in chemistry, biology, and physics—the study of genomes, extrasolar planets, even the intricacies of quantum systems. And all this before large language models such as ChatGPT came on the scene. We are living through a revolution in machine learning-powered AI that shows no signs of slowing down. This technology is based on relatively simple mathematical ideas, some of which go back centuries, including linear algebra and calculus, the stuff of seventeenth- and eighteenth-century mathematics. It took the birth and advancement of computer science and the kindling of 1990s computer chips designed for video games to ignite the explosion of AI that we see today. In this enlightening book, Anil Ananthaswamy explains the fundamental math behind machine learning, while suggesting intriguing links between artificial and natural intelligence. Might the same math underpin them both? As Ananthaswamy resonantly concludes, to make safe and effective use of artificial intelligence, we need to understand its profound capabilities and limitations, the clues to which lie in the math that makes machine learning possible. In a brand-new afterword exclusively in the paperback edition, Ananthaswamy dives into the Transformer architecture that makes large language models like ChatGPT possible and points to groundbreaking future directions enabled by the technology.
Why Machines Learn
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Author : Anil Ananthaswamy
language : en
Publisher: Random House
Release Date : 2024-07-16
Why Machines Learn written by Anil Ananthaswamy and has been published by Random House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-16 with Computers categories.
'An invaluable companion for anyone who wants a deep understanding of what’s under the hood of often inscrutable machines' Melanie Mitchell A rich, narrative explanation of the mathematics that has brought us machine learning and the ongoing explosion of artificial intelligence Machine-learning systems are making life-altering decisions for us: approving mortgage loans, determining whether a tumour is cancerous, or deciding whether someone gets bail. They now influence discoveries in chemistry, biology and physics - the study of genomes, extra-solar planets, even the intricacies of quantum systems. We are living through a revolution in artificial intelligence that is not slowing down. This major shift is based on simple mathematics, some of which goes back centuries: linear algebra and calculus, the stuff of eighteenth-century mathematics. Indeed by the mid-1850s, a lot of the groundwork was all done. It took the development of computer science and the kindling of 1990s computer chips designed for video games to ignite the explosion of AI that we see all around us today. In this enlightening book, Anil Ananthaswamy explains the fundamental maths behind AI, which suggests that the basics of natural and artificial intelligence might follow the same mathematical rules. As Ananthaswamy resonantly concludes, to make the most of our most wondrous technologies we need to understand their profound limitations - the clues lie in the maths that makes AI possible.
Machine Learning
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Author : VINOD CHANDRA, S.S.
language : en
Publisher: PHI Learning Pvt. Ltd.
Release Date : 2021-01-01
Machine Learning written by VINOD CHANDRA, S.S. and has been published by PHI Learning Pvt. Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-01 with Computers categories.
The present book is primarily intended for undergraduate and postgraduate students of computer science and engineering, information technology, and electrical and electronics engineering. It bridges the gaps in knowledge of the seemingly difficult areas of machine learning and nature inspired computing. The text is written in a highly interactive manner, which satisfies the learning curiosity of any reader. Content of the text has been diligently organized to offer seamless learning experience. The text begins with introduction to machine learning, which is followed by explanation of different aspects of machine learning. Various supervised, unsupervised, reinforced and nature inspired learning techniques are included in the text book with numerous examples and case studies. Different aspects of new machine learning and nature inspired learning algorithms are explained in-depth. The well-explained algorithms and pseudo codes for each topic make this book useful for students. The book also throws light on areas like prediction and classification systems. Key Features • Day to day examples and pictorial representations for deeper understanding of the subject • Helps readers easily create programs/applications • Research oriented approach • More case studies and worked-out examples for each machine learning algorithm than any other book
Python Machine Learning
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Author : Railey Brandon
language : en
Publisher: Roland Bind
Release Date : 2019-04-25
Python Machine Learning written by Railey Brandon and has been published by Roland Bind this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-25 with Computers categories.
★☆Have you come across the terms machine learning and neural networks in most articles you have recently read? Do you also want to learn how to build a machine learning model that will answer your questions within a blink of your eyes?☆★ If you responded yes to any of the above questions, you have come to the right place. Machine learning is an incredibly dense topic. It's hard to imagine condensing it into an easily readable and digestible format. However, this book aims to do exactly that. Machine learning and artificial intelligence have been used in different machines and applications to improve the user's experience. One can also use machine learning to make data analysis and predicting the output for some data sets easy. All you need to do is choose the right algorithm, train the model and test the model before you apply it on any real-world tool. It is that simple isn't it? ★★Apart from this, you will also learn more about★★ ♦ The Different Types Of Learning Algorithm That You Can Expect To Encounter ♦ The Numerous Applications Of Machine Learning And Deep Learning ♦ The Best Practices For Picking Up Neural Networks ♦ What Are The Best Languages And Libraries To Work With ♦ The Various Problems That You Can Solve With Machine Learning Algorithms ♦ And much more... Well, you can do it faster if you use Python. This language has made it easy for any user, even an amateur, to build a strong machine learning model since it has numerous directories and libraries that make it easy for one to build a model. Do you want to know how to build a machine learning model and a neural network? So, what are you waiting for? Grab a copy of this book now!
How Machines Learn Simplified Ai Concepts
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Author : Nova Martian
language : en
Publisher: Independently Published
Release Date : 2025-05-31
How Machines Learn Simplified Ai Concepts written by Nova Martian and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-31 with Computers categories.
In "How Machines Learn (Simplified AI Concepts): A Simple Guide to Big Ideas," readers embark on an accessible journey through the fundamentals of artificial intelligence and machine learning. The book begins by demystifying the nature of intelligence, mapping its evolution from human cognition to the algorithms powering modern technology. Through engaging historical context and real-world examples, it dismantles common myths, clarifies essential concepts, and explores how data and algorithms work in tandem to bring AI into our everyday lives. The guide methodically unpacks the building blocks of machine learning, covering supervised, unsupervised, and reinforcement learning in clear, understandable language. Each type is illustrated with relatable scenarios, such as spam detection and anomaly discovery, while illuminating core ideas like training, features, and dealing with common challenges such as bias or overfitting. Further, it introduces neural networks and deep learning, explaining both the transformative impact and the limitations of these technologies, as well as practical techniques for preparing data, evaluating models, and ensuring trustworthiness through explainable AI. Concluding with a thoughtful exploration of ethics, societal impact, and the future of AI, the book emphasizes responsible innovation and the enduring role of human judgment. It examines not only the opportunities brought by AI but also the critical questions around fairness, privacy, and accountability. Balancing technical clarity with big-picture insights, "How Machines Learn" is an ideal starting point for students, professionals, and enthusiasts eager to understand and thoughtfully navigate our increasingly AI-driven world.
Machine Learning For Beginners
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Author : Steven Cooper
language : en
Publisher: Roland Bind
Release Date : 2018-09-07
Machine Learning For Beginners written by Steven Cooper and has been published by Roland Bind this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-07 with Computers categories.
If you are looking for a complete beginners guide to learn machine learning with examples, in just a few hours, then you need to continue reading. Machine learning is an incredibly dense topic. It's hard to imagine condensing it into an easily readable and digestible format. However, this book aims to do exactly that. ★★ Grab your copy today and learn ★★ ♦ The different types of learning algorithm that you can expect to encounter ♦ The numerous applications of machine learning ♦ The different types of machine learning and how they differ ♦ The best practices for picking up machine learning ♦ What languages and libraries to work with ♦ The future of machine learning ♦ The various problems that you can solve with machine learning algorithms ♦ And much more... Starting from nothing, we slowly work our way through all the concepts that are central to machine learning. By the end of this book, you're going to feel as though you have an extremely firm understanding of what machine learning is, how it can be used, and most importantly, how it can change the world. You're also going to have an understanding of the logic behind the algorithms and what they aim to accomplish. Don't waste your time working with a book that's only going to make an already complicated topic even more complicated. Scroll up and click the buy now button to learn everything you need to know about Machine Learning!
Introduction To Machine Learning In The Cloud With Python
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Author : Pramod Gupta
language : en
Publisher: Springer Nature
Release Date : 2021-04-28
Introduction To Machine Learning In The Cloud With Python written by Pramod Gupta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-28 with Technology & Engineering categories.
This book provides an introduction to machine learning and cloud computing, both from a conceptual level, along with their usage with underlying infrastructure. The authors emphasize fundamentals and best practices for using AI and ML in a dynamic infrastructure with cloud computing and high security, preparing readers to select and make use of appropriate techniques. Important topics are demonstrated using real applications and case studies.
Artificial Intelligence
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Author : Christina Ahmet
language : en
Publisher: Shockwave Publishing via PublishDrive
Release Date : 2018-11-20
Artificial Intelligence written by Christina Ahmet and has been published by Shockwave Publishing via PublishDrive this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-20 with Computers categories.
Currently, Artificial Intelligence (AI) lives amongst the human population. They reside in smartphones. They help people find content on the internet. They learn the behavior of their owners and put out relevant, interesting content to enhance their owner's experience while they are browsing on the internet. In this book you will learn all about Artificial Intelligence and how it will affect your life in the near future. Learn exactly what Artificial Intelligence is Machine Learning AI and The Internet Of Things Opportunities for Artificial Intelligence Intelligent IoT and much much more!
Hands On Machine Learning With Tensorflow Js
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Author : Kai Sasaki
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-11-27
Hands On Machine Learning With Tensorflow Js written by Kai Sasaki and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-27 with Computers categories.
Hands-On Machine Learning with TensorFlow.js is a comprehensive guide that will help you easily get started with machine learning algorithms and techniques using TensorFlow.js. By the end of this book, you will be able to create and optimize your own web-based machine learning applications using practical examples.
Machine Learning For Cyber Physical Systems
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Author : Jürgen Beyerer
language : en
Publisher: Springer
Release Date : 2016-11-25
Machine Learning For Cyber Physical Systems written by Jürgen Beyerer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-25 with Technology & Engineering categories.
The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, September 29th, 2016. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.