Machine Learning finds application in areas as diverse as neuroscience, biomedical informatics, drug discovery,
speech recognition, language processing, computer vision, recommender systems, learning theory, robotics and games. In continutian to our previous series of summer schools this year's theme is "Deep Learing".
The ML summer school is slightly theoretical in nature but sufficient practical exercises would be covered to enable a better understanding of the theoretical track. Primary theme for this year’s summer school is chosen to be Deep Learning, seeing the recent trends of its rise. Experts in the field will deliver talks to share their views and works with the attendees and you are more than welcome to interact and discuss ideas with the speakers. It will also be a good platform to bounce ideas amongst other like-minded enthusiasts. The primary focus of the summer school this time would be on the more recent advancements in the field of Deep Learning.
- Co-located event: SUMMER SCHOOL ON COMPUTER VISION
The summer school is intended for graduate students working in the Machine Learning and related areas. Undergraduate students and people from industry looking for exposure or those working or planning to work in this area will also find the summer school beneficial. As such there are no strict prior requisites for the program but a basic understanding of Machine Learning is expected and a mathematical background never hurts.