Release Date:- 2025-09-02
Availability:- In Stock
Book of Jupyter Notebooks that implement and mathematically derive machine learning algorithms from first-principles. The output of each notebook is a visualization of the machine learning algorithm throughout its training phase, ultimately converging..
Release Date:- 2019-05-17
Availability:- In Stock
This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of..
Release Date:- 2024-03-04
Availability:- In Stock
This open access book provides a detailed review of the latest methods and applications of artificial intelligence (AI) and machine learning (ML) in medicine. With chapters focusing on enabling the reader to develop a thorough understanding of the key..
Release Date:- 2022-10-04
Availability:- In Stock
Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from..
Release Date:- 2023-07-24
Availability:- In Stock
This Open Access volume provides readers with an up-to-date and comprehensive guide to both methodological and applicative aspects of machine learning (ML) for brain disorders. The chapters in this book are organized into five parts. Part One presents..
Release Date:- 2024-06-28
Availability:- In Stock
Architect and run real-world AI/ML solutions at scale on Google Cloud, and discover best practices to address common industry challenges effectivelyKey FeaturesUnderstand key concepts, from fundamentals through to complex topics, via a methodical approac..
Release Date:- 2018-12-07
Availability:- In Stock
This report gives an introduction to the subject of artificial intelligence (AI) and suggestions for how the healthcare sector can begin to explore and understand it. The authors have studied the options for offering automated decision-making support..
Release Date:- 2025-04-09
Availability:- In Stock
This open access book presents the concept of Informed Machine Learning and demonstrates its practical use with a compelling collection of applications of this paradigm in industrial and business use cases. These range from health care over manufacturing..
Release Date:- 2024-12-04
Availability:- In Stock
Unravels common myths and simplifies complex ideas about AI, Machine Learning, Deep Learning, and Generative AI. This comprehensive e-book delves into the distinctions between Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL),..
Release Date:- 2015-05-12
Availability:- In Stock
Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure.This third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer c..
Release Date:- 2023-01-01
Availability:- In Stock
This open access book introduces and explains machine learning (ML) algorithms and techniques developed for statistical inferences on a complex process or system and their applications to simulations of chemically reacting turbulent flows.These two f..
Release Date:- 2020-11-18
Availability:- In Stock
Manusia adalah makhluk pembelajar yang memiliki kemampuan belajar yang sangat luar biasa. Proses pembelajaran tersebut telah dimulai sejak dia dilahirkan sampai akhir hayatnya. Seiring bertambah usia, manusia mulai mempelajari bagaimana cara berjalan,..
Release Date:- 2022-05-17
Availability:- In Stock
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..
Release Date:- 2017-10-03
User Average Rating:- 4.5
Availability:- In Stock
A collection of shockingly prescient stories covering topics from aliens to AI, including some that have never before been seen, from the New York Times best-selling author of the Silo trilogyHugh Howey is known for crafting riveting and immersive page-turner..
Release Date:- 2019-12-11
Availability:- In Stock
This Redpaper introduces the integration between two IBM products that you might like to consider when implementing a modern agile solution on your Z systems. The document briefly introduces Operational Decision Manager on z/OS and Machine learning on..
Release Date:- 2019-01-13
User Average Rating:- 4
Availability:- In Stock
Peter Norvig, Research Director at Google, co-author of AIMA, the most popular AI textbook in the world: "Burkov has undertaken a very useful but impossibly hard task in reducing all of machine learning to 100 pages. He succeeds well in choosing..
Release Date:- 2022-04-30
Availability:- In Stock
‘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 w..
Release Date:- 2025-10-22
Availability:- In Stock
The potential of machine learning today is extraordinary, yet many aspiring developers and tech professionals find themselves daunted by its complexity. Whether you're looking to enhance your skill set and apply machine learning to real-world projects..
Release Date:- 2015-04-02
Availability:- In Stock
This tutorial text gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches -which are based on optimization techniques – together with the Bayesian inference approach, whose essence lies in the use..
Release Date:- 2019-11-14
Availability:- In Stock
Machine Learning is an area of artificial intelligence involving the development of algorithms to discover trends and patterns in existing data; this information can then be used to make predictions on new data. A growing number of researchers and clinicians..
Release Date:- 2012-08-24
Availability:- In Stock
A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing m..
Release Date:- 2023-08-15
Availability:- In Stock
An advanced book for researchers and graduate students working in machine learning and statistics who want to learn about deep learning, Bayesian inference, generative models, and decision making under uncertainty.An advanced counterpart to Probabilistic M..
Release Date:- 2014-10-08
Availability:- In Stock
A Proven, Hands-On Approach for Students without a Strong Statistical FoundationSince the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing work on the statistical..
Release Date:- 2019-11-18
Availability:- In Stock
Machine Learning is an upcoming field with wide usage in dayto day life. There are a lot of problems which Machine learningsolves using a combination of statistics and a wide array ofdifferent algorithms. Here we aim at giving a brief introductionto a ..
Release Date:- 2017-11-20
Availability:- In Stock
Machine Learning: A Constraint-Based Approach provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that includes neural networks and kernel machines. The book pres..
Release Date:- 2016-08-19
Availability:- In Stock
Machine learning, one of the top emerging sciences, has an extremely broad range of applications. However, many books on the subject provide only a theoretical approach, making it difficult for a newcomer to grasp the subject material. This book provides..
Release Date:- 2014-05-31
Availability:- In Stock
Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides an extensive..
Release Date:- 2012-02-13
Availability:- In Stock
If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate useful tasks. Authors Drew Conway and John Myles..
Release Date:- 2014-09-26
Availability:- In Stock
Learn how to apply test-driven development (TDD) to machine-learning algorithms—and catch mistakes that could sink your analysis. In this practical guide, author Matthew Kirk takes you through the principles of TDD and machine learning, and shows you..
