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Machine Learning is advancing the civilization and is one of the key drivers of economy today. Machine Learning literacy may one day become essential the way computer literacy is today. This talk intends to explain Machine Learning concepts to wider audiences by using easy to relate real world analogies and applications. It serves as a refresher to the already initiated. A fundamental concept in machine learning is similarity. The dot product that is ubiquitously present in machine learning is a measure for similarity. Similarity is key to human learning as well. We learn in delta increments by comparing and contrasting with what we already know. Analogies or similarities help

Machine learning is an exciting field for many, but the rigor, math, and its rapid evolution are often found to be formidable, keeping them away from studying and pursuing a career in this area. This talk uses similarity to explain the underpinnings of machine learning to those who want to get insights into machine learning and data science. A number of concepts, techniques, and algorithms in machine learning will be explained relating them to real-world analogies in a way that audiences with little or no background in the area will also be able to appreciate.

Speaker: Dr. Vishnu S. Pendyala is a faculty member of the Department of Applied Data Science at San Jose State University and is the Chair of the IEEE CS, Silicon Valley Chapter. He has over two decades of experience with software industry leaders in the Silicon Valley, USA. During his recent 3 year term as an ACM Distinguished speaker and before that as a researcher and industry expert, he gave numerous (50+) invited talks. He holds MBA in Finance and PhD, MS, and BE degrees in Computer Engineering from US and Indian universities. Dr. Pendyala taught a one-week course sponsored by the Ministry of Human Resource Development (MHRD), Government of India, under the GIAN program in 2017 to Computer Science faculty from all over the country and delivered the keynote in a similar program sponsored by AICTE, Government of India in 2022.

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