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Machine Learning in Biotechnology and Life Sciences

You're reading from   Machine Learning in Biotechnology and Life Sciences Build machine learning models using Python and deploy them on the cloud

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Product type Paperback
Published in Jan 2022
Publisher Packt
ISBN-13 9781801811910
Length 408 pages
Edition 1st Edition
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Author (1):
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Saleh Alkhalifa Saleh Alkhalifa
Author Profile Icon Saleh Alkhalifa
Saleh Alkhalifa
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Table of Contents (17) Chapters Close

Preface 1. Section 1: Getting Started with Data
2. Chapter 1: Introducing Machine Learning for Biotechnology FREE CHAPTER 3. Chapter 2: Introducing Python and the Command Line 4. Chapter 3: Getting Started with SQL and Relational Databases 5. Chapter 4: Visualizing Data with Python 6. Section 2: Developing and Training Models
7. Chapter 5: Understanding Machine Learning 8. Chapter 6: Unsupervised Machine Learning 9. Chapter 7: Supervised Machine Learning 10. Chapter 8: Understanding Deep Learning 11. Chapter 9: Natural Language Processing 12. Chapter 10: Exploring Time Series Analysis 13. Section 3: Deploying Models to Users
14. Chapter 11: Deploying Models with Flask Applications 15. Chapter 12: Deploying Applications to the Cloud 16. Other Books You May Enjoy

Understanding the field of deep learning

As we mentioned in the introduction, deep learning is a subset or branch of the machine learning space that focuses on developing models using neural networks. The idea behind using neural networks for deep learning derives from neural networks found in the human brain. Let's learn more about this.

Neural networks

Similar to machine learning, the idea behind developing deep learning models is not to explicitly define the steps in which a decision or prediction is made. The main idea here is to generalize from the data. Deep learning makes this possible by drawing a parallel between the dendrites, cell body, and synapses of the human brain, which, within the context of deep learning, act as inputs, nodes, and outputs for a given model, as shown in the following diagram:

Figure 8.1 – Comparison between the human brain and a neural network

Some of the biggest benefits behind such an implementation revolve...

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