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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 to summer school's, this year's theme is "Machine Learning".
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. Seeing the recent trends of its rise, primary theme for this year’s summer school is chosen to be Deep Learning. Experts talks will be deliver where they will share the view 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 summer school is intended for graduate students working in 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 always helps.
Computer Vision is a rapidly evolving field with its applications being steadily integrated into our day to day lives. The field has received a wide interest from various stakeholders ranging from theoretical researchers, application designers and developers and even business entities. In continutian of our previous summer school's, this year's theme is "Computer Vision".
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