Book

Description

"Accelerating Drug Discovery: A Tutorial-Based Approach with Machine Learning" is a comprehensive and practical guide that explores the synergy between machine learning and drug discovery. Geared towards researchers, students, and professionals in the pharmaceutical industry, the book offers valuable insights into leveraging machine learning techniques to expedite the process of drug development. This book begins by laying a strong foundation in machine learning principles, ensuring readers of all levels to grasp the key concepts. It covers a wide array of machine learning algorithms, presenting each with clear tutorials. This hands-on approach enables readers to gain practical experience in implementing machine learning models for drug discovery applications. Throughout the chapters, it showcases the transformative impact of machine learning at various stages of drug discovery. From target data selection, data import, filtration, QSAR, model building and implementation in a workflow and enhancing decision-making. "Accelerating Drug Discovery: A Tutorial-Based Approach with Machine Learning" is an indispensable resource that equips readers with the knowledge and tools to leverage the full potential of machine learning in the field of drug discovery. By combining theory, tutorials, and real-world applications, the book empowers readers to embrace cutting-edge technologies and drive innovation in pharmaceutical research.