Practical Machine Learning with H2O: Powerful, Scalable Techniques for Deep Learning and AI
O'Reilly Media (9781491964606)
(9780262035613 / 45189572) - Country of publication: UNITED STATES - Dimensions: 229 x 178 x 32 mm - Format: 800 pages - Height: 187 mm - Spine width: 35 mm - Width: 237 mm - The MIT Press - In Print | Deep Learning techniques
Deep Learning (Adaptive Computation and Machine Learning Series) is an extensive guide to various aspects of deep learning, including its mathematical and conceptual foundations, industrial applications, and research prospects. The book is authored by three experts in the field - Yoshua Bengio, Ian Goodfellow, and Aaron Courville.
Deep learning is a subset of machine learning that involves training computers to learn from experience and understand the world through a hierarchy of concepts. It differs from traditional machine learning techniques because it does not require humans to explicitly define all the knowledge that the computer needs. Instead, the computer learns by building upon simpler concepts to form more complex ones, creating a multi-layered hierarchy.
This book provides an in-depth exploration of deep learning techniques used in industry and research, covering topics such as neural networks, convolutional networks, recurrent networks, and reinforcement learning. It also includes practical advice on how to implement these techniques in real-world applications.
Overall, Deep Learning (Adaptive Computation and Machine Learning Series) is a comprehensive resource for anyone interested in learning about this cutting-edge technology and its potential applications.
O'Reilly Media (9781491964606)
Packt Publishing (9781789955750)
MIT Press (9780262537551)
Packt Publishing (9781789955750)
MIT Press (9780262537551)