Deep Learning - A Comprehensive Guide

This book focuses on all the relevant topics of Deep Learning. It covers the conceptual, mathematical and practical aspects of deep learning & offers real time practical examples & case studies. It is aimed primarily at graduates, researchers and professionals working in Deep Learning.

List of contents

1. Introduction to Deep Learning. 2. The Tools and Prerequisites. 3. Machine Learning: The Fundamentals 4. The Deep Learning Framework. 5. CNN- Convolutional Neural Networks - A Complete Understanding. 6. CNN Architectures - An Evolution 7. Recurrent Neural Networks. 8. Autoencoders. 9. Generative Models. 10. Transfer Learning. 11. Intel OpenVino - A Must Know Deep Learning Toolkit. 12. Interview Questions and Answers.

Summary

This book focuses on all the relevant topics of Deep Learning. It covers the conceptual, mathematical and practical aspects of deep learning & offers real time practical examples & case studies. It is aimed primarily at graduates, researchers and professionals working in Deep Learning.

Product details

• Authors: Sini Raj Pulari, Shriram K Vasudevan, Subashri Vasudevan, Vasudevan Subashri
• Publisher: Taylor and Francis
• Languages: English
• Product format: Paperback / Softback
• Released: 04.10.2024
• EAN: 9781032028859
• ISBN: 978-1-032-02885-9
• No. of pages: 290
• Weight: 449 g
• Illustrations: schwarz-weiss Illustrationen, Raster,schwarz-weiss, Zeichnungen, schwarz-weiss, Tabellen, schwarz-weiss
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; machine learning, Data Mining, COMPUTERS / Machine Theory, Mathematical theory of computation, COMPUTERS / Data Science / Machine Learning, COMPUTERS / Data Science / Data Visualization, COMPUTERS / Data Science / Data Analytics, COMPUTERS / Database Administration & Management, Data capture and analysis, Data Capture & Analysis