Explore deep learning applications in this comprehensive lecture from the International Centre for Theoretical Sciences. Delve into the fundamentals of machine learning, including linear regression, gradient descent, and neural networks. Examine advanced topics such as convolutional neural networks, recurrent neural networks, and their applications in image and speech recognition. Gain insights into the theoretical aspects of deep learning, including non-convex optimization and low-rank approximation. Learn about cutting-edge research in the field, including recent findings on local minima in linear networks. Conclude with an overview of experimental results and a Q&A session to deepen your understanding of this rapidly evolving field.