Schedule

* = optional reading

Date	Topic	Readings / Videos	Assignments
09 Oct		* Deep Learning Book - Part I: Applied Math and Machine Learning Basics
16 Oct	MLPs, Gradient Descent & Backpropagation	Deep Learning Book - Chapter 6: Deep Feedforward Networks	First Steps
23 Oct	CNNs	Deep Learning Book - Chapter 9: Convolutional Networks, Sections 9.1 to 9.5	tf.data & Tensorboard
30 Oct	CNNs (cont.)	Deep Learning Book - Chapter 9: Convolutional Networks, remaining sections Reading Assignment	Basic CNNs & Keras
06 Nov	RNNs	Deep Learning Book - Chapter 10: Sequence Modeling: Recurrent and Recursive Nets, Sections 10.1 to 10.6	ResNet
13 Nov	RNNs (cont.)	Deep Learning Book - Chapter 10: Sequence Modeling: Recurrent and Recursive Nets, Sections 10.6, 10.7 and 10.10 to 10.12 Sequence Modeling With CTC	Sentiment Classification Part 1
20 Nov	Attention and Memory	Reading Assignment	Sentiment Classification Part 2
27 Nov	Word Embeddings & Language Models	Reading Assignment	Attention-based NMT
04 Dec	Introspection	Reading Assignment	Word2Vec
11 Dec	Autoencoders & Self-Supervised Representation Learning	Reading Assignment	Introspection
18 Dec	Regularization & Optimization	Deep Learning Book - Chapter 7: Regularization Deep Learning Book - Chapter 8: Optimization (except Section 8.6) * Regularization for Deep Learning: A Taxonomy	Self-supervised Learning
08 Jan	Practical Methodology	Deep Learning Book - Chapter 11: Practical Methodology Practical Methodology Talk by Ian Goodfellow Andrew Ng: Machine Learning Yearning
15 Jan	Graph Neural Networks	Reading Assignment	Adversarial Examples
22 Jan			Investigating Data Issues