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Results for 'ronald t kneusel'
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Practical Deep Learning, 2nd Edition
A Python-Based IntroductionRonald T. Kneusel earned a PhD in machine learning from the University of Colorado, Boulder, and has over 20 years of machine learning experience in industry. Kneusel is also the author of numerous books, including Math for Programming (2025), The Art of Randomness (2024), How AI Works (2023), Strange Code (2022), and Math for Deep Learning (2021), all from No Starch Press.
€ 64,50 -
How Deep Learning Works
An Experiment-First Guide for ProgrammersRonald T. Kneusel builds deep learning systems in industry and has extensive experience in medical imaging and medical-device development. He holds a PhD in computer science from the University of Colorado Boulder, along with degrees in physics and mathematics, and has been programming since the early days of personal computing. He is the author of several well-regarded books on computing, mathematics, and AI.
€ 74,95 -
Birding with AI
Concepts and Projects for OrnithologyBirding with AI introduces birders, ornithologists and related professionals to modern artificial intelligence as it applies to ornithology. The book explores existing AI-based birding tools and then delves into the essence of AI to build intuition, enabling readers to understand the projects that follow.
€ 82,95 -
Numbers and Computers
€ 87,95 -
Math for Programming
Ronald T. Kneusel has been working with machine learning in industry since 2003 and has a PhD in machine learning from the University of Colorado, Boulder. Kneusel is the author of Practical Deep Learning, Math for Deep Learning, The Art of Randomness, How AI Works, and Strange Code (all from No Starch Press), as well as Numbers and Computers and Random Numbers and Computers (Springer).
€ 62,50 -
How AI Works
From Sorcery to Science"Succinct and clear-cut . . . a beacon for those wanting to delve into the mesmerizing world of AI, offering a detailed yet comprehensible overview of the evolutionary trajectory of machine learning technologies, from their rudimentary forms to the pioneering entities of today."—Antoine Tardif, CEO, Unite.AI“A tour de force of the rich history of artificial intelligence . . . For beginners, it demystifies AI and is a perfect resource to get up to date with more than six decades of research and development. . . . Even AI experts will gain a fresh perspective, enhancing their understanding and ability to articulate complex concepts."—Ben Dickson, Software Engineer, Editor of TechTalks"Kneusel does a superb job of explaining the evolution and intricacies of artificial intelligence with a combination of clarity and wit . . . Anyone who wants to understand the concepts of artificial intelligence, as well as its limitations and possible pitfalls, along with the tremendous potential it has to transform technology and society over time should read How AI Works."—Tony Bradley, Editor-in-Chief, TechSpective“A friendly and personal peek behind the curtain of modern AI. Ronald T. Kneusel tells the story of how the field grew, and surveys the ideas that are powering the AI revolution. From this book, you'll learn not only how AI works today, but its limits, its capabilities, and where it might take us tomorrow.”—Andrew Glassner, Author of Deep Learning: A Visual Approach"A must-read for anyone wishing to dig into AI without getting lost in the weeds. Kneusel has succeeded in explaining how AI works to a layperson like myself."—Kenneth Gass, Honorary Curator of Geology, Milwaukee Public Museum“After reading this book, I have a better understanding of the ML tools I have already used in my work . . . I recommend this book to anyone who works with software systems, including management, and anyone who just wants to know what AI actually does under the hood.”—Daniel Kosey, CISSP, Cybersecurity Engineer"If all the hype and reporting about AI has piqued your curiosity, but you don’t want to wade through the math and equations, Ron Kneusel’s latest book is for you. . . . You will no doubt learn a lot as you make your way from the earliest ideas about AI to today’s best models that are knocking at the door of True AI."—David Gorodetzky, Senior Scientist, Machine Learning and Remote Sensing"An excellent starting point for the enthusiast and anyone who wants to know what AI is and will be. . . . The author has another hit science book on a fascinating and apropos topic."—David S. Mazel, Principal/Manager Systems Engineer, Regulus-Group "AI isn't magic. If you've ever wondered how it works, what it can do, or why there's so much hype, How AI Works will teach you everything you want to know."—Midwest Book Review
€ 39,95 -
The Art of Randomness
Randomized Algorithms in the Real World"The Art of Randomness is a useful reference and resource for anyone who needs to apply the power of randomized algorithms, including programmers, scientists, engineers, mathematicians, even artists and musicians...highly recommended."—Midwest Book Review
€ 66,50 -
Strange Code
Esoteric Languages That Make Programming Fun Again"[No Starch Press] had me at 'esolangs' . . . I am almost always a fan of a book that talks about how to build a programming language. This one not only talks about some of the concepts involved in doing that, and shows how to build two custom languages (Filska and Firefly), AND talks about a few popular esoteric languages and how they warp your brain in a good way, it takes the unusual step of examining some languages that Kneusel describes as 'atypical,' which have some interesting and useful properties. His coverage of CLIPS, alone, is worth the price of admission here. The knowledge gained here is foundational, and will help [you] with all sorts of different kinds of applications . . . I think every programmer should read it." —Ted Neward, "The Dude of Software," Principal, Neward & Associates; Technologist, Executive Leader, Speaker/Author"A fascinating and thought-provoking tour through programming languages. Strange Code guides you through some mostly forgotten languages—such as Forth, SNOBOL, and CLIPS—before exploring more experimental languages—such as Piet—where your source code is an image. I particularly enjoyed Firefly, a language for the BBC micro:bit, created especially for the book."—Sean McManus, Author of Mission Python: Code a Space Adventure Game!"[Gives] a grounding in the basics of concepts like Turing Completeness without leaving readers to fend for themselves in a forest of of dense computer science arcana. As a reference and source for teachers, Strange Code has much to commend it." —Terry Freedman, Teach Secondary magazine
€ 66,50 -
Math for Deep Learning
To truly understand the power of deel learning, you need to grasp the mathematical concepts that make it tick. "Math for deep learning" will give you a working knowledge of probability, statistics, linear algebra, and differential calculus-- the essential math subfields required to practice deep learning successfully. Each subfield is explained with Python code and hands-on, real-world examples that bridge the gap between pure mathematics and its applications in deep learning. The book begins with fundamentals such as Bayes' theorem before progressing to more advanced concepts like training neural networks using vectors, matrices, and derivatives of functions. You'll then put all this math to use as you explore and implement backpropagation and gradient descent-- the foundational algorithms that have enabled the AI revolution.
€ 47,00 -
Practical Deep Learning
This book is for people with no experience with machine learning and who are looking for an intuition-based, hands-on introduction to deep learning using Python.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 machine learning models, neural networks, and modern convolutional neural networks. Experiments in Python--working with leading open-source toolkits and standard datasets--give you hands-on experience with each model and help you build intuition about how to transfer the examples in the book to your own projects.You'll start with an introduction to the Python language and the NumPy extension that is ubiquitous in machine learning. Prominent toolkits, like sklearn and Keras/TensorFlow are used as the backbone to enable you to focus on the elements of machine learning without the burden of writing implementations from scratch. An entire chapter on evaluating the performance of models gives you the knowledge necessary to understand claims on performance and to know which models are working well and which are not. The book culminates by presenting convolutional neural networks as an introduction to modern deep learning. Understanding how these networks work and how they are affected by parameter choices leaves you with the core knowledge necessary to dive into the larger, ever-changing world of deep learning.
€ 56,00 -
Random Numbers and Computers
This book covers pseudorandom number generation algorithms, evaluation techniques, and offers practical advice and code examples.
€ 60,50 -
Random Numbers and Computers
This book covers pseudorandom number generation algorithms, evaluation techniques, and offers practical advice and code examples.
€ 87,95