Efficient Deep Learning: Foundations, Systems, and Applications

This course delves into the foundations of building efficient deep learning frameworks. The course starts with the basics of deep learning. Then, diverse efficient inference and training algorithms are discussed in this course, including sparsity, quantization, knowledge distillation, mixture-of-experts, distributed computing, etc. In the end, the curriculum introduces several promising applications, optimization foundations, and advanced topics.