efficient learning machines pdf

October 14, 2017

Efficient learning machines pdf is book written by Mariette Awad, and Rahul Khanna and published by The Expert Voice Machine Learning. This book consists of 263 pages including title pages. This book contains 11 chapters starting from Machine Learning, Machine Learning and Knowledge Discovery, Support Vector Machines for Classification, Support Vector Regression, Hidden Markov Model, Bio-Inspired Computing: Swarm Intelligence, Deep Neural Networks, Cortical Algorithms, Deep Learning, Multi objective Optimization, and Machine Learning in Action: Examples. The complete name of the book is: Efficient Learning Machines: Theories, Concepts, and Applications for Engineers and System Designers because in this book theories, concepts and how to design Machine in a efficient way is studied and explained.

efficient learning machines pdf

About the Authors:

Prof. Mariette Awad is an associate professor in the Electrical and Computer Engineering Department of the American University of Beirut. She is a visiting professor at Virginia Commonwealth University, Intel Mobile Group, and MIT and she received her PhD in electrical engineering in 2007. She was invited by Google, CVC labs, and Qualcomm to present her work on machine learning and image processing. She has published a book “Efficient Machine Learning” in 2015 as well as in various conferences and journals and is managing few awards. She is an active member in IEEE and reviewer for IEEE transactions. Earlier to her academic position, she was with IBM System and Technology group in Vermont as a wireless product engineer. Over the years, her technical leadership and innovative spirit has earned her management recognition, several business awards, and multiple patents at IBM. The complete detailed about her experience, research interest, and experience is giving in the following link:


Rahul Khanna is a principal engineer functioning as a platform architect at Intel involved in the development of energy-efficient algorithms. Over the past 20 years he has worked on server system software technologies, including platform automation, power/thermal optimization techniques, reliability, and predictive methodologies. Dr. Khanna is a member of the IEEE and the receiver of three Intel Achievement Awards for his supports in areas related to the advancement of platform technologies. He holds Masters and PhD in electrical and computer engineering. He is also the inventor of the Intel Interconnect Built in self-test (IBIST), a methodology for high-speed interconnect testing. The complete details about rahul khanna is giving in the following link:


conclusion of efficient learning machines pdf:

Efficient Learning Machines pdf provides engineers, students of engineering, and system designers with the knowledge and guidance to design and create new and more efficient machine learning systems. This book is useful in solving multi-objective optimization problems with no dominated methods that minimize distance to the Pareto front. The machine learning techniques most commonly used to resolve complex real-world problems.

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