Pro Deep Learning with TensorFlow 2.0 A Mathematical Approach to Advanced Artificial Intelligence in Python

This book builds upon the foundations established in its first edition, with updated chapters and the latest code implementations to bring it up to date with Tensorflow 2.0. Pro Deep Learning with TensorFlow 2.0 begins with the mathematical and core technical foundations of deep learning. Next, you...

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Bibliographic Details
Main Author: Pattanayak, Santanu
Format: eBook
Published: Berkeley, CA Apress 2023, 2023
Edition:2nd ed. 2023
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • Chapter 1: Mathematical Foundations
  • Chapter 2: Introduction to Deep learning Concepts and Tensorflow 2.0
  • Chapter 3: Convolutional Neural networks
  • Chapter 4: Natural Language Processing
  • Chapter 5: Unsupervised Learning with Restricted Boltzmann Machines and Auto-encoders
  • Chapter 6: Advanced Neural Networks