Apress, 2018. — 362 p. — ISBN: 1484235630. Code files only! Bridge the gap between a high-level understanding of how an algorithm works and knowing the nuts and bolts to tune your models better. This book will give you the confidence and skills when developing all the major machine learning models. In Pro Machine Learning Algorithms, you will first develop the algorithm in...
Packt, 2020. — 256 p. — ISBN: 9781789801781. !Code files only Create, train, and evaluate various machine learning models such as regression, classification, and clustering using ML.NET, Entity Framework, and ASP.NET Core Key Features Get well-versed with the ML.NET framework and its components and APIs using practical examples Learn how to build, train, and evaluate popular...
Packt Publishing, 2018. — 500 p. — ISBN: 1509304444. !Only code files Unleash Google's Cloud Platform to build, train and optimize machine learning models Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine...
Packt Publishing, 2019. — 360 p. — ISBN: 978-1-83864-535-9. Code files only! This friendly and accessible guide to AI theory and programming in Python requires no maths or data science background. AI is changing the world – and with this book, anyone can start building intelligent software! Through his best-selling video courses, Hadelin de Ponteves has taught hundreds of...
Packt Publishing, 2019. — 456 p. — ISBN: 1789136364. Code files only! A guide to advances in machine learning for financial professionals, with working Python code. Machine Learning for Finance explores new advances in machine learning and shows how they can be applied across the financial sector, including in insurance, transactions, and lending. It explains the concepts and...
Packt, 2018. — 503 p. — ISBN: 178934641X. Code files only! The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book...
2nd Edition. — Aaron Jones, Christopher Kruger, Benjamin Johnston. — Packt Publishing Limited, July 2020. — 549 p. — ISBN: 978-1-80020-070-8. Code files only! With the help of interesting examples and activities, learn how to apply unsupervised algorithms on unlabelled datasets Do you find it difficult to learn how big companies like WhatsApp and Amazon find valuable insight...
3rd edition. — Packt Publishing, 2020. — 527 p. — ISBN 9781800209718. A comprehensive guide to get you up to speed with the latest developments of practical machine learning with Python and upgrade your understanding of machine learning (ML) algorithms and techniques Key Features Dive into machine learning algorithms to solve the complex challenges faced by data scientists...
Manning Publications Co, 2021. — 493 p. — ISBN 9781617295645. Code Files Only! At its core, machine learning is about efficiently identifying patterns and relationships in data. Many tasks, such as finding associations among terms so you can make accurate search recommendations or locating individuals within a social network who have similar interests, are naturally expressed...
O’Reilly, 2019. - 362p. - ISBN: 1492035645 !Code files only Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning cannot be applied. Unsupervised learning, on the other hand, can be...
2nd Edition. — Packt Publishing Ltd., 2020. — 579 p. — ISBN: 978-1-83921-153-9. Code files only! Understand the fundamentals and develop your own AI solutions in this updated edition packed with many new examples. Artificial intelligence (AI) has the potential to replicate humans in every field. Artificial Intelligence by Example serves as a starting point for you to understand...
Packt Publishing Ltd., 2020. — 404 p. — ISBN: 978-1-78995-608-5. Code files only! Use the power of deep learning with Python to build and deploy intelligent web applications When used effectively, deep learning techniques can help you develop intelligent web apps. In this book, you’ll cover the latest tools and technological practices that are being used to implement deep...
Apress, 2017. - 358p. - ISBN: 978-1484228654 Code files only! Master machine learning with Python in six steps and explore fundamental to advanced topics, all designed to make you a worthy practitioner. This book’s approach is based on the “Six degrees of separation” theory, which states that everyone and everything is a maximum of six steps away. Mastering Machine Learning...
O’Reilly Media, 2020. — 432 p. — ISBN: 978-1-492-07305-5. Code files only! Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You’ll examine ML concepts and over 20 case studies in...
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