The Mathematics of Deep Learning Part 2
Welcome to Part 2 of 'The Mathematics of Deep Learning' series! In this video, Dr. Ernesto Lee, a faculty member in Data Analytics at Miami Dade College, continues his exploration of the mathematical principles that underlie deep learning. Building on the fundamentals covered in Part 1, Dr. Lee delves deeper into the world of linear algebra, calculus, probability theory, and statistics, and their applications in deep learning. From calculus to Bayesian statistics, this video provides a comprehensive understanding of the math needed to build and train complex neural networks. Join us on this journey through the fascinating world of deep learning and discover the power of mathematics in artificial intelligence!