Produs

Machine Learning and AI Beyond the Basics - Sebastian Raschka

Name: Machine Learning and AI Beyond the Basics - Sebastian Raschka
Brand: Sebastian Raschka
Price: 276.42 RON
Availability: InStock

Vânzător

libris.ro

Cumpără

Pret

276.42 Lei 345.53 Lei

Categorie (vânzător)

Computers

Marca

Sebastian Raschka

Produs actualizat în urmă cu 1 lună

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Machine Learning and AI Beyond - Disponibil la libris.ro

Pe YEO găsești Machine Learning and AI Beyond de la Sebastian Raschka, în categoria Computers.

Indiferent de nevoile tale, Machine Learning and AI Beyond the Basics - Sebastian Raschka din categoria Computers îți poate aduce un echilibru perfect între calitate și preț, cu avantaje practice și moderne.

Preț: 276.42 Lei

Caracteristicile produsului Machine Learning and AI Beyond

Brand: Sebastian Raschka
Categoria: Computers
Magazin: libris.ro
Ultima actualizare: 22-04-2026 00:26:07

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Descriere magazin:
Learn the answers to 30 cutting-edge questions in machine learning and AI and level up your expertise in the field. nIf you\'ve locked down the basics of machine learning and AI and want a fun way to address lingering knowledge gaps, this book is for you. This rapid-fire series of short chapters addresses 30 essential questions in the field, helping you stay current on the latest technologies you can implement in your own work. n nEach chapter of Machine Learning and AI Beyond the Basics asks and answers a central question, with diagrams to explain new concepts and ample references for further reading. This practical, cutting-edge information is missing from most introductory coursework, but critical for real-world applications, research, and acing technical interviews. You won\'t need to solve proofs or run code, so this book is a perfect travel companion. You\'ll learn a wide range of new concepts in deep neural network architectures, computer vision, natural language processing, production and deployment, and model evaluation, including how to: n nn n- Reduce overfitting with altered data or model modifications n- Handle common sources of randomness when training deep neural networks n- Speed up model inference through optimization without changing the model architecture or sacrificing accuracy n- Practically apply the lottery ticket hypothesis and the distributional hypothesis n- Use and finetune pretrained large language models n- Set up k-fold cross-validation at the appropriate time nYou\'ll also learn to distinguish between self-attention and regular attention; name the most common data augmentation techniques for text data; use various self-supervised learning techniques, multi-GPU training paradigms, and types of generative AI; and much more. nWhether you\'re a machine learning beginner or an experienced practitioner, add new techniques to your arsenal and keep abreast of exciting developments in a rapidly changing field.n

Machine Learning and AI Beyond the Basics - Sebastian Raschka - 0 | YEO

Machine Learning and AI Beyond the Basics - Sebastian Raschka - 0 | YEO

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