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Deep Learning for Genomics

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

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Product type Paperback
Published in Nov 2022
Publisher Packt
ISBN-13 9781804615447
Length 270 pages
Edition 1st Edition
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Author (1):
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Upendra Kumar Devisetty Upendra Kumar Devisetty
Author Profile Icon Upendra Kumar Devisetty
Upendra Kumar Devisetty
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Toc

Table of Contents (18) Chapters Close

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 17. Other Books You May Enjoy

Technical requirements

In this chapter, we will discuss some tools and software that are essential for model deployment and model monitoring. Let’s go over the technical specifications.

Streamlit

Streamlit (https://streamlit.io/) is an open source framework for building web apps based on Python. It is a faster way to build and share web apps in minutes using Python, which fits in very well with DL frameworks such as Keras. The main advantage of Streamlit compared to other frameworks is it is easy to build, quick to deploy a model in a cloud environment, and previous knowledge of the frontend is not required. It is best suited for data scientists or genomic researchers who are not web developers and they don’t need to spend their time learning web development to build apps. Streamlit enables them to quickly build a web app and share it with their collaborators, which they can run to make predictions or classifications without any knowledge of DL. Unlike other frameworks...

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