Machine Learning (ML)


Machine Learning for Business Analytics: Concepts, Techniques, and Applications with Analytic Solver Data Mining. 4 Ed - Galit Shmueli, Kuber R. Deokar, Nitin R. Patel, Peter C. Bruce (2023)

 Machine learning―also known as data mining or predictive analytics―is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information.

 Machine Learning for Business Analytics: Concepts, Techniques, and Applications with Analytic Solver® Data Mining provides a comprehensive introduction and an overview of this methodology. The fourth edition of this best-selling textbook covers both statistical and machine learning algorithms for …

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Building Computer Vision Applications Using ANNs. 2 Ed - Shamshad (Sam) Ansari (2023)

 Computer vision is constantly evolving, and this book has been updated to reflect new topics that have emerged in the field since the first edition’s publication. All code used in the book has also been fully updated.

 This second edition features new material covering image manipulation practices, image segmentation, feature extraction, and object identification using real-life scenarios to help reinforce each concept. These topics are essential for building advanced computer …

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Антология машинного обучения. Важнейшие исследования в области ИИ за последние 60 лет - Терренс Джозеф Сейновски (2022)

 История машинного обучения, от теоретических исследований 50-х годов до наших дней, в изложении ведущего мирового специалиста по изучению нейросетей и искусственного интеллекта Терренса Сейновски.

 Автор рассказывает обо всех ключевых исследованиях и событиях, повлиявших на развитие этой технологии, начиная с первых конгрессов, посвященных искусственному разуму и заканчивая глубоким обучением и возможностями, которые оно предоставляет разработчикам ИИ.

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GoLang for Machine Learning: A Hands-on-Guide to Building Efficient, Smart and Scalable ML Models with Go Programming - Evan Atkins (2024)

 Go, the high-performance language from Google, is rapidly gaining traction in the machine learning world. Its speed, concurrency, and built-in features make it ideal for building efficient, scalable ML models. But where do you start?

 This book is written by a seasoned developer and machine learning expert, providing you with practical, hands-on guidance based on real-world experience. After reading this book, you'll be equipped with the knowledge and …

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