Practical Machine Learning
Practical Machine Learning
The talk will be an introduction to the Fundamentals of Machine Learning and its jargons, understanding big data, tasks, tools, real-world applications and a tour of the following learning algorithms:
• Decision Tree Based Learning
• Kernel Methods Based Learning
• Regression Based Learning
• Bayesian Learning
• Deep Learning
Date and Time
Location
Hosts
Registration
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- Stony Brook University
- Stony Brook , New York
- United States
- Building: Frey Hall
- Room Number: 305
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- Co-sponsored by Stony Brook Electrical & Computer Engineering Department
- Starts 20 October 2018 12:53 AM UTC
- Ends 13 November 2018 10:00 PM UTC
- No Admission Charge
Speakers
Dr. Vibha Mane of Stony Brook Electrical & Computer Engineering Department
Practical Machine Learning
Biography:
Vibha Mane has a PhD in Electrical Engineering from Stony Brook University, and a B.S. and an M.S. in Physics from University of Connecticut. For her dissertation at Stony Brook University, she developed a new approach, based on propagating the moments of the distribution, to derive an approximate solution of the master equation. This approach helps simulate complex biochemical networks, which would otherwise be infeasible with the customary Monte Carlo techniques.
Dr. Mane is currently an Adjunct Faculty in the Department of Electrical and Computer Engineering, performing teaching, research and curriculum development for Machine Learning courses.
Agenda
6:30-7:00pm Registration, Light Refreshments and Networking
7-8pm Practical Machine Learning seminar