The course covers theoretical concepts such as inductive bias, the PAC learning framework, Bayesian learning methods, margin-based learning, and Occam's Razor.
Anyone who is interested in learning Machine Learning.
Students entering the class are expected to have a pre-existing working knowledge of probability, linear algebra, statistics and algorithms, though the class has been designed to allow students with a strong numerate background to catch up and fully participate.
We will be making a drowsiness detecting device. A countless number of people drive on the highway day and night.
Anyone who is interested in learning Machine Learning.
Students entering the class are expected to have a pre-existing working knowledge of probability, linear algebra, statistics and algorithms, though the class has been designed to allow students with a strong numerate background to catch up and fully participate.
We will use Deep Learning to accurately identify the gender and age of a person from a single image of a face.
Anyone who is interested in learning Machine Learning.
Students entering the class are expected to have a pre-existing working knowledge of probability, linear algebra, statistics and algorithms, though the class has been designed to allow students with a strong numerate background to catch up and fully participate.
