Date	Location	Topic	Notes	Reading
Week 1
2021-10-27 10:00-12:00	zoom	Introduction	[slides] [printable] [video]	Deep Learning Book (Ch. 1, 2, 3)
2021-10-28 13:00-15:00	zoom	Machine learning with Spark	[slides] [printable] [video]	Spark Book (Ch. 24, 25)
Week 2
2020-11-03 10:00-12:00	zoom	Machine Learning - Regression	[slides] [printable] [video]	Deep Learning Book (Ch. 4, 5) Handson Book (Ch. 2, 4) Spark Book (Ch. 27)
2020-11-04 14:00-16:00	zoom	Machine Learning - Classification	[slides] [printable] [video]	Deep Learning Book (Ch. 4, 5) Handson Book (Ch. 3) Spark Book (Ch. 26)
2020-11-06 13:00-15:00	zoom	Lab1	[notebook] [video-spark] [video-docker]
Week 3
2021-11-17 10:00-12:00	More on Supervised Learning	[slides] [printable]	Handson Book (Ch. 6, 7) Spark Book (Ch. 27)
2021-11-18 08:00-10:00	Deep Feedforward Networks	[printable] [notebook]	Deep Learning Book (Ch. 6) Handson Book (Ch. 10)
2021-11-19 08:00-10:00	Lab2	[slides] [colab]
Week 4
2021-11-24 10:00-12:00	Training Feedforward Networks	[printable] [notebook]	Deep Learning Book (Ch. 7, 8) Handson Book (Ch. 11)
2021-11-25 08:00-10:00	Convolutional Neural Networks	[slides] [printable] [notebook]	Deep Learning Book (Ch. 9) Handson Book (Ch. 14) 10 CNN Architectures [link]
2021-11-26 08:00-10:00	zoom	Lab3	[notebook] [video]
Week 5
2021-12-01 10:00-12:00	zoom	Recurrent Neural Networks	[printable] [notebook]	Deep Learning Book (Ch. 10) Handson Book (Ch. 15, 16) Understanding LSTM Networks [link]
2021-12-02 08:00-10:00	Attention and Transformer Lecturer: Francisco J. Pena	[slides] [colab]	Attention Is All You Need [paper] Mechanics of Seq2seq Models With Attention [link] The Illustrated Transformer [link]
Week 6
2021-12-08 10:00-12:00	Distributed Learning - Part 1	[printable]	Communication-Efficient Distributed Deep Learning: A Comprehensive Survey [paper] The TensorFlow Partitioning and Scheduling Problem [paper] Device Placement Optimization with Reinforcement Learning [paper] A Hierarchical Model for Device Placement [paper]
2021-12-09 10:00-12:00	Distributed Learning - Part 2 Lecturer: Jim Dowling	[slides]
Week 7
2021-12-15 10:00-12:00	Distributed Learning - Part 3	[printable]	Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent [paper] The Hidden Vulnerability of Distributed Learning in Byzantium [paper] SGD: Decentralized Byzantine Resilience [paper] Fast Machine Learning with Byzantine Workers and Servers [paper]