Introduction to "Learning Deep Learning"

This training introduces the book "Learning Deep Learning" (LDL) from NVIDIA Deep Learning Institute (DLI). "LDL" was published by Pearson in 2021 and teaches deep learning from scratch to people with a programming or computer science/engineering background. Without requiring any prior machine learning skills, "LDL" starts the first chapter with describing an individual artificial neuron. The remaining chapters build upon this single neuron, while alternating theory and programming. "LDL" includes programming examples of networks for natural language translation and image captioning, and detailed descriptions of important image and language processing networks such as VGGNet, Inception, ResNet, Mask R-CNN, BERT, and GPT. The talk begins with a high-level description of the topics covered by "LDL". It then moves on to a more detailed description of some of the content in the initial chapters, including a couple of programming examples. It concludes with an overview of a more complex application, an image captioning network, that generates textual descriptions of images. This image captioning network is the focus of one of the final programming examples in "LDL," and gives a flavor of the type of skills the reader will master after reading the book. Prerequisite(s): Programming (preferably Python but not required) 

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