Overview

If you're ready to venture beyond introductory concepts and dig deeper into machine learning, deep learning, and AI, the question-and-answer format of Machine Learning Q and AI will make things fast and easy for you, without a lot of mucking about. Born out of questions often fielded by author Sebastian Raschka, the direct, no-nonsense approach of this book makes advanced topics more accessible and genuinely engaging. Each brief, self-contained chapter journeys through a fundamental question in AI, unraveling it with clear explanations, diagrams, and hands-on exercises. WHAT'S INSIDE- FOCUSED CHAPTERS- Key questions in AI are answered concisely, and complex ideas are broken down into easily digestible parts. WIDE RANGE OF TOPICS- Raschka covers topics ranging from neural network architectures and model evaluation to computer vision and natural language processing. PRACTICAL APPLICATIONS- Learn techniques for enhancing model performance, fine-tuning large models, and more. You'll also explore how to- . Manage the various sources of randomness in neural network training . Differentiate between encoder and decoder architectures in large language models . Reduce overfitting through data and model modifications . Construct confidence intervals for classifiers and optimize models with limited labeled data . Choose between different multi-GPU training paradigms and different types of generative AI models . Understand performance metrics for natural language processing . Make sense of the inductive biases in vision transformers If you've been on the hunt for the perfect resource to elevate your understanding of machine learning, Machine Learning Q and AI will make it easy for you to painlessly advance your knowledge beyond the basics. Learn the answers to 30 cutting-edge questions in machine learning and AI and level up your expertise in the field. If you're ready to venture beyond introductory concepts and dig deeper into machine learning, deep learning, and AI, the question-and-answer format of Machine Learning Q and AI will make things fast and easy for you, without a lot of mucking about. Born out of questions often fielded by author Sebastian Raschka, the direct, no-nonsense approach of this book makes advanced topics more accessible and genuinely engaging. Each brief, self-contained chapter journeys through a fundamental question in AI, unraveling it with clear explanations, diagrams, and hands-on exercises. WHAT'S INSIDE- FOCUSED CHAPTERS- Key questions in AI are answered concisely, and complex ideas are broken down into easily digestible parts. WIDE RANGE OF TOPICS- Raschka covers topics ranging from neural network architectures and model evaluation to computer vision and natural language processing. PRACTICAL APPLICATIONS- Learn techniques for enhancing model performance, fine-tuning large models, and more. You'll also explore how to- . Manage the various sources of randomness in neural network training . Differentiate between encoder and decoder architectures in large language models . Reduce overfitting through data and model modifications . Construct confidence intervals for classifiers and optimize models with limited labeled data . Choose between different multi-GPU training paradigms and different types of generative AI models . Understand performance metrics for natural language processing . Make sense of the inductive biases in vision transformers If you've been on the hunt for the perfect resource to elevate your understanding of machine learning, Machine Learning Q and AI will make it easy for you to painlessly advance your knowledge beyond the basics.

Full Product Details

9781718503762

Table of Contents

Reviews

“Sebastian has a gift for distilling complex, AI-related topics into practical takeaways that can be understood by anyone. His new book, Machine Learning and AI Beyond the Basics, is another great resource for AI practitioners of any level.” –Cameron R. Wolfe, Writer of Deep (Learning) Focus “Sebastian uniquely combines academic depth, engineering agility, and the ability to demystify complex ideas. He can go deep into any theoretical topics, experiment to validate new ideas, then explain them all to you in simple words. If you’re starting your journey into machine learning, Sebastian is your guide.” –Chip Huyen, Author of Designing Machine Learning Systems “Sebastian Raschka's new book, Machine Learning Q and AI, is a one-stop shop for overviews of crucial AI topics beyond the core covered in most introductory courses...If you have already stepped into the world of AI via deep neural networks, then this book will give you what you need to locate and understand the next level.” –Ronald T. Kneusel, author of How AI Works

“Sebastian has a gift for distilling complex, AI-related topics into practical takeaways that can be understood by anyone. His new book, Machine Learning and AI Beyond the Basics, is another great resource for AI practitioners of any level.” –Cameron R. Wolfe, Writer of Deep (Learning) Focus “Sebastian uniquely combines academic depth, engineering agility, and the ability to demystify complex ideas. He can go deep into any theoretical topics, experiment to validate new ideas, then explain them all to you in simple words. If you’re starting your journey into machine learning, Sebastian is your guide.” –Chip Huyen, Author of Designing Machine Learning Systems

Author Information

Sebastian Raschka, PhD, is a machine learning and AI researcher with a passion for education. As Lead AI Educator at Lightning AI, he is excited about making AI and deep learning more accessible. Raschka previously was Assistant Professor of Statistics at the University of Wisconsin-Madison, where he specialized in researching deep learning and machine learning, and is the author of the bestselling books Python Machine Learning and Machine Learning with PyTorch and Scikit-Learn. You can find out more about his research on his website at https-//sebastianraschka.com.

Tab Content 6

Customer Reviews

Recent Reviews

Countries Available