Introduction to Machine Learning

This session will explain the what, the why and the how of Machine Learning (ML), one of the most vibrant and fast-growing fields in technology today. It will describe the technical and business reasons behind the importance of ML in industry and research. The talk will show how ML relates to the fields of Artificial Intelligence (AI) and Computational Statistics, and describe three main categories of learning algorithms – supervised, unsupervised and reinforcement learning. Some learning algorithms such as regression analysis and decision tree building are examined in more detail. The presentation will conclude with some commonly used open source software that can be used to start your ML journey.

Dr. Pragyansmita Nayak is Technical and Data Architect in the Momentum Product Development Group at CGI Federal Inc. She has over 18+ yrs of experience and holds a Ph.D. in Computational Sciences and Informatics (under the esteemed guidance of Prof. Kirk Borne at GMU, Fairfax, VA) and a Bachelors in Computer Science (BITS Pilani, India). Her Ph.D. thesis focused on the application of Machine Learning techniques (Generalized Linear Model and Bayesian Networks) on the estimation of the Photomorphic Redshift of the galaxies. She previously worked with Novell India, Wipro Global R&D, and IIT Madras ERNET PoP. She is an avid meetup and hackathon participant. She won the 2016 AngelHack DC HPE Haven OnDemand(HOD) challenge. She won the best graduate poster prize at the 2015 Mid-Atlantic Sigma Xi competition. She receives rave reviews on her presentations involving data science and technical architecture and is a Dataversity presenter.?