ATI804: Machine Learning II

This course will provide you with (i) the foundations of Deep Learning, understand how to build neural networks; (ii) a solid introduction to the field of RL, the core challenges and approaches in the field, including generalization and exploration. And learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. 

Topics to be covered include; Foundations of neural networks and deep learning: Techniques to improve neural networks: regularization and optimizations and deep learning frameworks; Convolutional Neural Networks and its applications (e.g. object classification, object detection, face verification, style transfer); Recurrent Neural Networks and its applications (e.g. natural language processing, speech recognition).