Python Programming: Basics to Machine Learning

This comprehensive text on Python programming is designed for undergraduate and postgraduate students in Computer Science and Information Technology. Whether you are a beginner or have limited programming knowledge, this book offers a structured learning experience, starting from foundational concepts and advancing to complex topics like machine learning. Divided into three parts, the book ensures a smooth progression from Basics and Core concepts of Python to Machine Learning with Python. It covers fundamental topics such as data types, variables, operators, and interactive input-output, enabling readers to write simple yet effective Python programs. Subsequently, the text explores advanced concepts like control flow, functions, file handling, object-oriented programming, modules, and data visualization through graph plotting empowering readers to develop robust and complex Python applications. Finally, the book introduces its readers to the world of machine learning, covering essential topics like data preprocessing, supervised and unsupervised learning, and implementing algorithms. The book equips students to excel in Python programming and seamlessly transition into machine learning, enabling them to design and implement customized algorithms for their datasets.

Lalita Kumari is Assistant Professor at the Amity School of Engineering and Technology (ASET), Amity University, Patna. Also, she has served NIT Agartala for 10 years as a faculty of Computer Science and Engineering. She holds an M.Tech. in Computer Science and Engineering from CDAC Noida and a Ph.D. in Engineering from NIT Agartala. A highly accomplished academic with a long experience of teaching UG and PG students, she is both GATE and UGC-NET qualified. An active researcher and innovator, Dr. Lalita holds multiple patents and has published numerous research papers in reputed journals and conferences, including those indexed in Scopus and IEEE. Her areas of interest include Artificial Intelligence, Machine Learning, Natural Language Processing, Image Processing, Advanced Algorithms, and Theory of Computation.