Dive into Deep Learning

Dive into Deep Learning book cover

Dive into Deep Learning

Author(s): Aston Zhang (Author), Zachary C. Lipton (Author), Mu Li (Author), Alexander J. Smola (Author)

  • Publisher: Cambridge University Press
  • Publication Date: December 7, 2023
  • Edition: 1st
  • Language: English
  • Print length: 574 pages
  • ISBN-10: 1009389432
  • ISBN-13: 9781009389433

Book Description

Deep learning has revolutionized pattern recognition, introducing tools that power a wide range of technologies in such diverse fields as computer vision, natural language processing, and automatic speech recognition. Applying deep learning requires you to simultaneously understand how to cast a problem, the basic mathematics of modeling, the algorithms for fitting your models to data, and the engineering techniques to implement it all. This book is a comprehensive resource that makes deep learning approachable, while still providing sufficient technical depth to enable engineers, scientists, and students to use deep learning in their own work. No previous background in machine learning or deep learning is required―every concept is explained from scratch and the appendix provides a refresher on the mathematics needed. Runnable code is featured throughout, allowing you to develop your own intuition by putting key ideas into practice.

Editorial Reviews

Review

‘In less than a decade, the AI revolution has swept from research labs to broad industries to every corner of our daily life. Dive into Deep Learning is an excellent text on deep learning and deserves attention from anyone who wants to learn why deep learning has ignited the AI revolution: the most powerful technology force of our time.’ Jensen Huang, Founder and CEO, NVIDIA

‘This is a timely, fascinating book, providing not only a comprehensive overview of deep learning principles but also detailed algorithms with hands-on programming code, and moreover, a state-of-the-art introduction to deep learning in computer vision and natural language processing. Dive into this book if you want to dive into deep learning!’ Jiawei Han, Michael Aiken Chair Professor, University of Illinois at Urbana-Champaign

‘This is a highly welcome addition to the machine learning literature, with a focus on hands-on experience implemented via the integration of Jupyter notebooks. Students of deep learning should find this invaluable to become proficient in this field.’ Bernhard Schölkopf,, Director, Max Planck Institute for Intelligent Systems

Book Description

An approachable text combining the depth and quality of a textbook with the interactive multi-framework code of a hands-on tutorial.

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