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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

Chapter 4: Visualizing Data with Python

Regardless of the field of work you operate in, the career path you've chosen, or the specific project you are working on, the ability to effectively communicate information to others will always be useful. In fact, exactly one hundred years ago, in 1921, Frederick R. Barnard first said something which has become a phrase you have probably heard countless times: A picture is worth a thousand words.

With the many new technologies that have emerged in the realm of machine learning in recent years, the amount of data being structured, processed, and analyzed has grown exponentially. The ability to take data in its raw form and translate it to a meaningful and communicative diagram is one of the most sought-after skill sets in the industry today. Most decisions made in large companies and corporations are generally data-driven, and the best way to start a conversation about an area you care about is to create a meaningful visualization about...

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