Advanced Deep Learning with TensorFlow 2 and Keras: Apply DL, GANs, VAEs, deep RL, unsupervised learning, object detection and segmentation, and more, 2nd Edition
Author: Rowel Atienza (Author)
Publisher finelybook 出版社: Packt Publishing
Edition 版本: 2nd ed. edition
Publication Date 出版日期: 2020-02-28
Language 语言: English
Print Length 页数: 512 pages
ISBN-10: 1838821651
ISBN-13: 9781838821654
Book Description
Book Description
Review
“Great visuals, code, and math. The book delivers what the deep learning practitioner needs: advanced content with replicable and reproducible results. I highly recommend this great book by Rowel Atienza.”
—
Bernardo F. Nunes, PhD, Lead Data Scientist, Growth Tribe Academy
“Advanced Deep Learning with TensorFlow 2 and Keras – Second Edition is a good and big step into an advanced practice direction. It’s a brilliant book and consider this as a must-read for all.”
—
Dr. Tristan Behrens, Founding Member of AI Guild and Independent Deep Learning Hands-On Adviser
“I highly recommend this book for the curious data practitioner who wants to further solidify their knowledge of deep learning. The companion GitHub code repository is very useful and provides a hassle-free way to actually experiment with the various ideas presented in the book. If you enjoy reading technical books, but also enjoy experimenting with real code, and didn’t think the two could be combined effectively – this book is here to change your perspective!”
—
Danny Ma, Data Science Leader, Founder of Sydney Data Science & #DataWithDanny – an online community for aspiring data professionals
About the Author
Rowel Atienza is an Associate Professor at the Electrical and Electronics Engineering Institute of the University of the Philippines, Diliman. He holds the Dado and Maria Banatao Institute Professorial Chair in Artificial Intelligence and received his MEng from the National University of Singapore for his work on an AI-enhanced four-legged robot. He finished his Ph.D. at The Australian National University for his contribution in the field of active gaze tracking for human-robot interaction. His current research work focuses on AI and computer vision.
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