Deep Learning and Neural Networks

In this course, you will learn all about neural networks and deep learning.

In the first chapter, you’ll learn about predictive neural networks, including CNNs (for images) and RNNs (for text).

In the second chapter, you’ll learn about generative neural networks, including RBMs, Autoencoders, GANs, and Hopfield Networks.

In the third chapter you’ll learn about the mathematical foundations of neural networks, including the Universal Approximation Theorem and Kolmogorov-Arnold Networks.