Random variables in machine learning / Dr. Piratla Srihari -- Analysis of EMG signals using extreme learning machine with nature inspired feature selection techniques / A. Anitha and Bakiya Ambikapathy -- Detection of breast cancer by using various machine learning and deep learning algorithms / Yogesh Jadhav, Harsh Mathur -- Assessing the radial efficiency performance of bus transport sector using data envelopment analysis / Swati Goyal, Shivi Agarwal, Trilok Mathur and Nirbhay Mathur.

"Technology is moving at an exponential pace in this era of computational intelligence. Machine Learning has emerged as one of the most promising tools used to challenge and think beyond current limitations. This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques. This handbook focuses on new Machine Learning developments that can lead to newly developed applications. It uses a predictive and futuristic approach which makes Machine Learning a promising tool for processes and sustainable solutions. It also promotes newer algorithms which are more efficient and reliable for new dimensions in discovering other applications and then goes on to discuss the potential in making better use of machines in order to ensure optimal prediction, execution, and decision-making. Individuals looking for Machine Learning based knowledge will find interest in this handbook. The readership ranges from undergraduate students of engineering and allied courses to researchers, professionals, and application designers"-- Provided by publisher.

OCLC-licensed vendor bibliographic record.