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Key benefits

Learn the applications of machine learning in biotechnology and life science sectors

Discover exciting real-world applications of deep learning and natural language processing

Understand the general process of deploying models to cloud platforms such as AWS and GCP

Description

The booming fields of biotechnology and life sciences have seen drastic changes over the last few years. With competition growing in every corner, companies around the globe are looking to data-driven methods such as machine learning to optimize processes and reduce costs. This book helps lab scientists, engineers, and managers to develop a data scientist's mindset by taking a hands-on approach to learning about the applications of machine learning to increase productivity and efficiency in no time. You’ll start with a crash course in Python, SQL, and data science to develop and tune sophisticated models from scratch to automate processes and make predictions in the biotechnology and life sciences domain. As you advance, the book covers a number of advanced techniques in machine learning, deep learning, and natural language processing using real-world data. By the end of this machine learning book, you'll be able to build and deploy your own machine learning models to automate processes and make predictions using AWS and GCP.

Who is this book for?

This book is for data scientists and scientific professionals looking to transcend to the biotechnology domain. Scientific professionals who are already established within the pharmaceutical and biotechnology sectors will find this book useful. A basic understanding of Python programming and beginner-level background in data science conjunction is needed to get the most out of this book.

What you will learn

Get started with Python programming and Structured Query Language (SQL)

Develop a machine learning predictive model from scratch using Python

Fine-tune deep learning models to optimize their performance for various tasks

Find out how to deploy, evaluate, and monitor a model in the cloud

Understand how to apply advanced techniques to real-world data

Discover how to use key deep learning methods such as LSTMs and transformers

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

Frequently bought together

€43.99

Machine Learning in Biotechnology and Life Sciences

€41.99

€33.99

Total € 119.97

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Amazon verified reviews

Faina Ryvkin Jan 28, 2022

This new book offers a comprehensive introduction to machine learning tools and data mining in a context of modern biotechnology and data science terminology, presenting a classification of machine learning techniques, surveying the mathematical foundation and main software applications such as expert level of Phyton. It presents illustrative examples of machine learning applications in biology and biotechnology, as well as the challenges and opportunities in these fields. The book might be helpful in other fields as the adoption of data-intensive machine-learning methods can lead to more evidence-based decision-making across health care, education, financial modeling, and marketing. I found this book to be well-organized, logical and clear in the delivery of the material. It can be easily used for self-education as well as for the classroom teaching. I wish, however, the content was divided into parts clearly indicating the introductory and advanced materials to facilitate its reading for the beginners.

Amazon Verified review

Jose Manuel Otero Jan 28, 2022

I have personally worked with Saleh on a meaningful drug development/discovery effort, and have benefited first-hand from his insights, analysis, and expertise. While I am not in expert in the development and/or applications of machine learning in biotechnology/biopharmaceutical research, I'm quite confident that Saleh is representing the current cutting edge methods being employed in world-class industrial research settings. If you don't have the opportunity to work with Saleh, as I have, this book is the next best option.Jose M. Otero, PhDChief Technology Officer at Turnstone Biologics, IncAdvisor and Consultant to various Life Science Organizations

Keith Baillargeon Feb 08, 2022

The author's scientific background offers invaluable insight and structure for practically employing machine learning and data science concepts to a wide variety of applications. The text, organization, and step-by-step tutorials (with images!) make the content extremely accessible—and more importantly—digestible.If you're in academia or industry and looking to move beyond the basic principles of programming, then follow along with Saleh as he guides you through complex concepts with ease.Keith Baillargeon, PhD

Ultimate Reviewer Jul 16, 2022

This is a great guide for anyone who wants to get into Biotechnology and life sciences.Some more examples in image Data would have been great. Overall a good resource to learn.

Nicholas Shepard Mar 17, 2022

Alkhalifa sets out to provide a complete one stop shop for readers to get started with ML in the life sciences. Despite this ambitious of a goal, as a master's student in Computer Science working in the Clinical Data Management field, I can say he has done just that. The content of this book communicates a large breadth of concepts with such clarity that it has made me wish it could have been the first step in my journey instead of having just read it. I am truly in awe of his ability to present such difficult concepts in a way that readers can understand and implement immediately- whether it was something completely new to me or something I thought I already new quite a bit about. I know this book will be invaluable as a tool to continually upskill myself and a comprehensive reference going forward in the field.

Machine Learning in Biotechnology and Life Sciences: Build machine learning models using Python and deploy them on the cloud

What do you get with eBook?