東北数學雑誌 PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download 東北数學雑誌 PDF full book. Access full book title 東北数學雑誌 by Tsuruichi Hayashi. Download full books in PDF and EPUB format.
Author: Tsuruichi Hayashi
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 232
Get Book Here
Book Description
Author: Tsuruichi Hayashi
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 232
Get Book Here
Book Description
Author:
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 558
Get Book Here
Book Description
Author: Stckvagn
Publisher:
ISBN: 9781419053597
Category : Adult education
Languages : en
Pages : 0
Get Book Here
Book Description
Author:
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 764
Get Book Here
Book Description
Author:
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 628
Get Book Here
Book Description
Comprises a trend report and abstracts under each topic; contributed by various authors.
Author: William F. Pinar
Publisher: Routledge
ISBN: 1136831126
Category : Education
Languages : en
Pages : 568
Get Book Here
Book Description
Continuing its calling to define the field and where it is going, the Second Edition of this landmark handbook brings up to date its comprehensive reportage of scholarly developments and school curriculum initiatives worldwide, providing a panoramic view of the state of curriculum studies globally. Its international scope and currency and range of research and theory reflect and contribute significantly to the ongoing internationalization of curriculum studies and its growth as a field worldwide. Changes in the Second Edition: Five new or updated introductory chapters pose transnational challenges to key questions curriculum research addresses locally. Countries absent in the First Edition are represented: Chile, Colombia, Cypress, Ethiopia, Germany, Iran, Luxembourg, Nigeria, Peru, Poland, Portugal, Singapore, South Africa, Spain, and Switzerland. 39 new or updated chapters on curriculum research in 34 countries highlight curriculum research that is not widely known in North America. This handbook is an indispensable resource for prospective and practicing teachers, for curriculum studies scholars, and for education students around the world.
Author:
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 428
Get Book Here
Book Description
Author:
Publisher:
ISBN:
Category : United States
Languages : en
Pages : 3728
Get Book Here
Book Description
Author: Library of Congress. Copyright Office
Publisher: Copyright Office, Library of Congress
ISBN:
Category : Copyright
Languages : en
Pages : 1510
Get Book Here
Book Description
Author: Ian Goodfellow
Publisher: MIT Press
ISBN: 0262337371
Category : Computers
Languages : en
Pages : 801
Get Book Here
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.
