PYTHON for Machine Learning- Step-by-Step Code Explanations and Practical ML Applications

About the Book: In todays rapidly evolving technological landscape the fusion of Python programming and Artificial Intelligence (AI) has unlocked endless opportunities for innovation and problem-solving. Python for Machine Learning: A Beginners Guide is crafted as an essential companion for anyone embarking on a journey into the world of AI and machine learning (ML). Whether you are an absolute beginner a student or a professional looking to enhance your technical skill set this book offers a structured hands-on approach to understanding and applying Python in AI-driven applications. Pythons rise as a dominant language in AI and ML is no coincidence. Its simplicity versatility and robust ecosystem of libraries make it the ideal choice for both beginners and experienced developers. The book begins by guiding you through the fundamentals of Python programming ensuring a smooth transition from basic coding to the development of intelligent systems. Your learning journey starts with setting up your development environment and writing your first Python program. From there you''ll explore essential programming constructsdata types control structures and functionsbefore progressing to data handling with powerful libraries such as NumPy and Pandas. The book then delves into more advanced topics including machine learning algorithms artificial neural networks (ANNs) and deep learning implementations using TensorFlow and Keras. Designed with a learn-by-doing philosophy each chapter is packed with step-by-step code explanations hands-on exercises and real-world projects to solidify your understanding. By the end of the book you will be proficient in Python and well-equipped with the knowledge and confidence to tackle AI and ML challenges head-on. We hope this book serves as a valuable resource in your learning journey inspiring you to explore innovate and make your mark in the ever-expanding field of artificial intelligence. About the Author: About Likewin Thomas Likewin Thomas is an accomplished Associate Professor and Head of AI & ML at PESITM Shivamogga. He holds a Ph.D. and M.Tech from NITK Surathkal and a B.E. from VTU. With 17+ years of experience he is a senior IEEE Member ISTE Life Member and former secretary of IEEE Mangalore Sub-Section. Currently he mentors the IEEE Student Branch and Google Developer Students Club. His expertise spans AI ML Big Data Data Analysis and Cloud Computing with proficiency in Python and Matlab. He has edited books for Taylor & Francis authored book chapters and published extensively in IEEE Springer and ACM. Likewin has secured research grants from VGST DST AICTE and TEQIP. He has organized numerous workshops and contributed to over 50 international and national events. His research interests include Robotics Drone Technology and IoT. About Sandeep Telkar Sandeep Telkar is an Assistant Professor in AI & ML at PESITM Shivamogga pursuing a Ph.D. from VTU Belgaum. He holds an M.Tech from GIT Belgaum and has 12+ years of experience. A member of IEI and a lifetime ISTE member he also mentors the Google Developer Students Club. His expertise includes AI ML Big Data Analytics Data Analysis and Python Programming. He has taught subjects like Discrete Mathematical Structures Data Structures Cloud Computing Design and Analysis of Algorithms Analog & Digital Electronics Microcontrollers & Embedded Systems and Database Management Systems. About Shilpa K C Mrs. Shilpa K C is an Assistant Professor in AI & ML at PESITM Shivamogga with over a decade of experience. She holds an M.Tech from STJIT Ranebennur and is pursuing a Ph.D. in one-shot learning for agriculture. With nearly five years of research experience her expertise includes AI Image Processing ML Graph Theory and One-shot Learning. A member of the Institute of Engineers (IE) she has authored research papers book chapters and patents. Dedicated to research teaching and mentoring she inspires students and professionals alike driving advancements in AI and computer science through her innovative work.