We are excited to kick off our first Embedded ML workshop - a combination of presentation and ideathon. https://www.meetup.com/Machine-Learning-Tokyo/
Firstly, we will talk about the promise of light-weight deep neural networks for energy-efficient and low-cost IoT applications. We discuss some examples of accelerated and low-memory version of deep learning models for real-time use, predictive maintenance, time-series analysis, and demand forecast. We focus on AI methods for turning IoT data into insights and actions.
After the introductory talk about Edge AI we will build teams of 3-5 people and have 1.5 hours to come up with project ideas for embedded ML scenarios that include use case, feasibility assessment, workflow, allocation of resources (human, time, computation, ...).
-- AGENDA --
- 12:30 pm Doors open
- 1:00 pm - 1:45 pm Talk: "AI for Embedded Computing: Towards low-power Edge Inference", Hossein I. Rad
- 1:45 pm - 2:00 pm Edge AI Ideathon, Yoovraj Shinde
- 2:00 pm - 2:45 pm Team building break with snacks and drinks
- 2:45 pm - 4:15 pm Ideathon
- 4:15 pm - 5:00 pm Presentations
- 5:00 pm Wrap up
-- MLT EDGE AI TEAM --
Hossein Izadi Rad is a Ph.D. candidate of Information Science and Technology with the University of Tokyo. He has an M.E. degree in Electrical Engineering. His recent works are concerned with off-the-cloud time-series prediction and demand forecast. He has collaborated with several tech startups in Tokyo.
Yoovraj Shinde is the Co-Founder of MLT and currently working as Technologist at Rakuten Institute of Technology. Electronics Engineer by heart, but worked in software industry for about 8 years. Worked on FrontEnd, BackEnd Java systems, iOS app development. His interests are Machine Learning and Robotics.
