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Can I read Deep Learning for Genomics : Data-driven Approaches for Genomics Applications in Life Sciences and Biotechnology on EtoBox?

Deep Learning for Genomics : Data-driven Approaches for Genomics Applications in Life Sciences and Biotechnology by Devisetty; Upendra Kumar is a nonfiction available to read on EtoBox.

What is Deep Learning for Genomics : Data-driven Approaches for Genomics Applications in Life Sciences and Biotechnology about?

Learn concepts, methodologies, and applications of deep learning for building predictive models from complex genomics data sets to overcome challenges in the life sciences and biotechnology industries Key Features Apply deep learning algorithms to solve real-world problems in the field of genomics Extract biological insights from deep learning models built from genomic datasets Train, tune, evaluate, deploy, and monitor deep learning models for enabling predictions in genomics Book Description Deep learning has shown remarkable promise in the field of genomics; however, there is a lack of a skilled deep learning workforce in this discipline. This book will help researchers and data scientists to stand out from the rest of the crowd and solve real-world problems in genomics by developing the necessary skill set. Starting with an introduction to the essential concepts, this book highlights the power of deep learning in handling big data in genomics. First, you'll learn about conventional genomics analysis, then transition to state-of-the-art machine learning-based genomics applications, and finally dive into deep learning approaches for genomics. The book covers all of the important

Who reads Deep Learning for Genomics : Data-driven Approaches for Genomics Applications in Life Sciences and Biotechnology?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Devisetty; Upendra Kumar
Publisher
Packt Publishing, Limited
Published
2022
Language
EN
ISBN
9781804615447
Category
nonfiction
Subjects
Computer Science, Science, Biology

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