Leaner and Greener AI with Quantization in PyTorch - Suraj Subramanian

This course on Leaner and Greener AI with Quantization in PyTorch aims to teach learners how to make AI models lighter, more power-efficient, and faster by implementing quantization techniques in PyTorch. The course covers the process of rounding FP32 parameters to integers without compromising model accuracy. The teaching method includes a video presentation by an ML engineer and developer advocate, with key topics such as the importance of efficient AI, different quantization techniques in PyTorch, workflow for quantization, and a Q&A session. This course is intended for individuals interested in optimizing AI models for improved performance and efficiency.