Intro to Deep Learning and Generative Models Course - Deep Learning News #3, Feb 13 2021

Sebastian's books: https://sebastianraschka.com/books/ Link to resources mentioned in the video: (2) High-Performance Large-Scale Image Recognition Without Normalization: https://arxiv.org/abs/2102.06171 (3.1) Deep Learning Theory: https://old.reddit.com/r/MachineLearning/comments/lgsgz8/d_deep_learning_theory/ (3.2) Double Descent: https://openai.com/blog/deep-double-descent/ (4) Removing biased data to improve fairness and accuracy: https://arxiv.org/abs/2102.03054 (5) TracIn — A Simple Method to Estimate Training Data Influence https://ai.googleblog.com/2021/02/tracin-simple-method-to-estimate.html (6.1) This human genome does not exist: Researchers taught an AI to generate fake DNA: https://thenextweb.com/neural/2021/02/08/this-human-genome-does-not-exist-researchers-taught-an-ai-to-generate-fake-dna/ (6.2) Creating artificial human genomes using generative neural networks: https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1009303 (7) https://www.vogue.com/article/rebag-launches-clair-ai-image-recognition-tool