Introduction to Deep Learning - Full Stack Deep Learning - March 2019

Embark on a whirlwind journey through the fundamentals of AI and deep learning in this introductory lecture by Professor Pieter Abbeel. Explore the revolutionary impact of deep learning across various domains, from image recognition to autonomous driving and speech recognition. Delve into the historical context of deep learning's evolution and understand its key components, including data processing and computational requirements. Gain insights into the course structure, content development process, and the significance of network size in deep learning applications. This lecture sets the stage for a comprehensive exploration of full-stack deep learning, providing a solid foundation for both beginners and experienced practitioners in the field.

Intro
Motivation
ImageNet
ImageNet Performance
ImageNet Examples
Car Driving
Speech Recognition
History of Deep Learning
Data
Data Processing
Compute
Why take this class
Time for breaks
Developing the content
Schedule
Network Size