logo
Product categories

EbookNice.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link.  https://ebooknice.com/page/post?id=faq


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookNice Team

(Ebook) The Science of Deep Learning by Drori, Iddo ISBN 9781108835084, 9781108883375, 9781108890441, 1108835082, 1108883370, 110889044X

  • SKU: EBN-54524354
Zoomable Image
$ 32 $ 40 (-20%)

Status:

Available

5.0

16 reviews
Instant download (eBook) The Science of Deep Learning after payment.
Authors:Drori, Iddo
Pages:360 pages.
Year:2022
Editon:New
Publisher:Cambridge University Press
Language:english
File Size:49.7 MB
Format:pdf
ISBNS:9781108835084, 9781108883375, 9781108890441, 1108835082, 1108883370, 110889044X
Categories: Ebooks

Product desciption

(Ebook) The Science of Deep Learning by Drori, Iddo ISBN 9781108835084, 9781108883375, 9781108890441, 1108835082, 1108883370, 110889044X

Up-to-date guide to deep learning with unique content, rigorous math, unified notation, comprehensive algorithms, and high-quality figures.The Science of Deep Learning emerged from courses taught by the author that have provided thousands of students with training and experience for their academic studies, and prepared them for careers in deep learning, machine learning, and artificial intelligence in top companies in industry and academia. The book begins by covering the foundations of deep learning, followed by key deep learning architectures. Subsequent parts on generative models and reinforcement learning may be used as part of a deep learning course or as part of a course on each topic. The book includes state-of-the-art topics such as Transformers, graph neural networks, variational autoencoders, and deep reinforcement learning, with a broad range of applications. The appendices provide equations for computing gradients in backpropagation and optimization, and best practices in scientific writing and reviewing. The text presents an up-to-date guide to the field built upon clear visualizations using a unified notation and equations, lowering the barrier to entry for the reader. The accompanying website provides complementary code and hundreds of exercises with solutions.
*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

Related Products