Author: United States. Congress. House. Committee on AppropriationsPublisher:
ISBN:
Category :
Languages : en
Pages : 1284
Book Description
Hearings
Author: United States. Congress. House. Committee on AppropriationsPublisher:
ISBN:
Category :
Languages : en
Pages : 1284
Book Description
Hearings
Author: United States. Congress. HousePublisher:
ISBN:
Category :
Languages : en
Pages : 2698
Book Description
A Bibliography for the International Geophysical Year
Author: Lee Anna EmbreyPublisher:
ISBN:
Category : Geophysics
Languages : en
Pages : 76
Book Description
An Interim Bibliography on the International Geophysical Year
Author: Publisher: National Academies
ISBN:
Category : International Geophysical Year, 1957-1958
Languages : en
Pages : 68
Book Description
National Science Foundation
Author: United States. Congress. House. AppropriationsPublisher:
ISBN:
Category :
Languages : en
Pages : 210
Book Description
Meteorological Abstracts and Bibliography
Author: Publisher:
ISBN:
Category : Atmospheric chemistry
Languages : en
Pages : 2030
Book Description
Includes supplements.
Public Works Appropriations for 1960
Author: United States. Congress. House. Committee on AppropriationsPublisher:
ISBN:
Category : Public works
Languages : en
Pages : 1794
Book Description
National Science Foundation, National Academy of Sciences
Author: United States. Congress. House. Committee on AppropriationsPublisher:
ISBN:
Category : International Geophysical Year, 1957-1958
Languages : en
Pages : 218
Book Description
Deep Learning
Author: Ian GoodfellowPublisher: MIT Press
ISBN: 0262337371
Category : Computers
Languages : en
Pages : 801
Book Description
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “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.
Chronique de l'U.G.G.I.
Author: International Union of Geodesy and GeophysicsPublisher:
ISBN:
Category : Geodesy
Languages : en
Pages : 336
Book Description