Deep Learning, Hardcover/Ian Goodfellow

Descriere YEO:

Deep Learning, Hardcover/Ian Goodfellow - Disponibil la elefant.ro

Pe YEO găsești Deep Learning, Hardcover/Ian Goodfellow de la Mit Press, în categoria Foreign Books.

Indiferent de nevoile tale, Deep Learning, Hardcover/Ian Goodfellow din categoria Foreign Books îți poate aduce un echilibru perfect între calitate și preț, cu avantaje practice și moderne.

Preț: 499.76 Lei

Caracteristicile produsului Deep Learning, Hardcover/Ian Goodfellow

• Brand: Mit Press
• Categoria: Foreign Books
• Magazin: elefant.ro
• Ultima actualizare: 12-12-2024 01:26:12

Comandă Deep Learning, Hardcover/Ian Goodfellow Online, Simplu și Rapid

Prin intermediul platformei YEO, poți comanda Deep Learning, Hardcover/Ian Goodfellow de la elefant.ro rapid și în siguranță. Bucură-te de o experiență de cumpărături online optimizată și descoperă cele mai bune oferte actualizate constant.

Descriere magazin:
``Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.`` -- Elon Musk , cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.