In fact, artificial neural networks were outputting distributions! We’re making the introductory section on MLE, AE, and VAE from TTD: To The Diffusion available for free. Understand neural network outputs and loss functions through maximum likelihood estimation, then connect PCA and autoencoders to latent-variable-based image generation and why VAEs are necessary. A total of 5 lessons, approximately 2 hours and 26 minutes.

How do RNNs process sequential information? We’re releasing the RNN section of TTT: To The Transformer for free. Gain an intuitive understanding of how recurrent neural networks work and build a foundation for studying attention and transformers.

How does GPT predict the next word and continue writing a sentence? We’re releasing Part 1 of the GPT section of ATT: After The Transformer for free. Understand how language models generate sentences through intuitive explanations, and build a foundation for studying GPT in greater depth.

Have you learned CNNs but feel unsure about how convolution finds features in images? We’re offering the CNN review section from Hyukpendheim’s Legend 13 for free. Instead of simply memorizing the model architecture, understand how CNNs work through intuitive explanations.