Introduction to IoT with Machine Learning and Image Processing using Raspberry Pi; First Edition by Shrirang Ambaji Kulkarni instant download
Machine Learning, a branch of Artificial Intelligence, is influencing society, industry and academia at large. The adaptability of Python programming language to Machine Learning has increased its popularity further. Another technology on the horizon is the Internet of Things (IoT). This book tries to address IoT, Python and Machine Learning along with a brief introduction to Image Processing. If you are a novice programmer or have just started exploring the IoT or Machine Learning with Python, this book is for you.
Features:
Raspberry Pi as IoT is described along with procedures for installation and configuration.
A simple introduction to Python Programming Language, along with its popular library packages like NumPy, Pandas, SciPy and Matplotlib, are explained exhaustively along with relevant examples.
Machine Learning with Python Scikit-Learn library is explained with an emphasis on supervised learning and classification.
Image processing on IoT is introduced for an audience who loves to apply Machine Learning algorithms to Images.
This book follows a hands-on approach and provides a huge collection of Python programs.
About the Authors
Dr. Shrirang Ambaji Kulkarni is a prolific learner, author and faculty member with over 18 years of experience in the field of Computer Science and Engineering. He currently works as an Associate Professor at the National Institute of Engineering in the Department of Computer Science and Engineering, Mysore, India.
Dr. Varadraj Gurpur is an eminent faculty member and researcher in the field of Health Informatics. He has authored many research articles in reputed journals. He currently works as an Associate Professor at the University of Central Florida in the Department of Health Informatics, Florida, USA.
Dr. Steven Lawrence Fernandes is a high-profile researcher in the field of Image Processing. He currently works as a Post-Doctoral Fellow at the University of Central Florida in the Department of Computer Science and Engineering, Florida,
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