You're reading from Deep Learning for Genomics Data-driven approaches for genomics applications in life sciences and biotechnology

Product type Paperback

Published in Nov 2022

Publisher Packt

ISBN-13 9781804615447

Length 270 pages

Edition 1st Edition

Concepts

Deep Learning

Author (1):

Upendra Kumar Devisetty

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Table of Contents (18) Chapters

Preface

1. Part 1 – Machine Learning in Genomics

2. Chapter 1: Introducing Machine Learning for Genomics FREE CHAPTER

3. Chapter 2: Genomics Data Analysis

4. Chapter 3: Machine Learning Methods for Genomic Applications

5. Part 2 – Deep Learning for Genomic Applications

6. Chapter 4: Deep Learning for Genomics

7. Chapter 5: Introducing Convolutional Neural Networks for Genomics

8. Chapter 6: Recurrent Neural Networks in Genomics

9. Chapter 7: Unsupervised Deep Learning with Autoencoders

10. Chapter 8: GANs for Improving Models in Genomics

11. Part 3 – Operationalizing models

12. Chapter 9: Building and Tuning Deep Learning Models

13. Chapter 10: Model Interpretability in Genomics

14. Chapter 11: Model Deployment and Monitoring

15. Chapter 12: Challenges, Pitfalls, and Best Practices for Deep Learning in Genomics

16. Index

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You're reading from Deep Learning for Genomics Data-driven approaches for genomics applications in life sciences and biotechnology

Table of Contents (18) Chapters

Introduction to Biopython for genomic data analysis

What is Biopython?

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You're reading from Deep Learning for Genomics Data-driven approaches for genomics applications in life sciences and biotechnology

Table of Contents (18) Chapters

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