Lectures

Time: MWF 12:00pm – 12:50pm
Lecture given live and recorded for asynchronous viewing. Live participation welcome but not required.
Zoom Link: https://brown.zoom.us/j/96237682852
Zoom Password: The name of our beloved lamp/bear who has recently departed campus to explore deep space (all lowercase)
Note: You must be logged into Zoom via your Brown account to access the Zoom meeting, as well as to access the lecture recordings.

Date Topic Slides Recording
Week 1 Introduction
Wed, 9/9 Introduction to deep learning pptx | pdf | pdf↓ video
Fri, 9/11 MNIST & Perceptrons pptx | pdf | pdf↓ video
Week 2 Deep Learning Fundamentals
Mon, 9/14 Loss functions, cross entropy loss, backprop pptx | pdf | pdf↓ video
Wed, 9/16 Backprop continued pptx | pdf | pdf↓ video
Fri, 9/18 Automatic differentiation, Brunoflow pptx | pdf | pdf↓ video
Week 3 Feed-Forward Neural Networks + Tensorflow
Mon, 9/21 Brunoflow continued, matrix representation of NNs + GPUs pptx | pdf | pdf↓ video
Wed, 9/23 The life cycle of machine learning systems pptx | pdf | pdf↓ video
Fri, 9/25 Intro to Tensorflow pptx | pdf | pdf↓ video
Week 4 Convolutional Neural Networks 1
Mon, 9/28 Activation functions, multilayer NN's
Practical neural net miscellanea
Higher-rank tensors + tensordot
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Wed, 9/30 Convolution and CNNs pptx | pdf | pdf↓ video
Fri 10/2 Multi-layer CNNs pptx | pdf | pdf↓ video
Week 5 CNNs, Language Models
Mon, 10/5 CNNs in the Real World pptx | pdf | pdf↓ video
Wed, 10/7 Language models, word embeddings pptx | pdf | pdf↓ video
Fri, 10/9 Overfitting and regularization, algorithmic fairness pptx | pdf | pdf↓ video
Week 6 Language Models, Recurrent Networks
Mon, 10/12 No class (Indigenous Peoples' Day)
Weds, 10/14 Feedforward language models pptx | pdf | pdf↓ video
Fri, 10/16 Recurrent neural networks pptx | pdf | pdf↓ video
Week 7 Recurrent Networks, Sequence-to-Sequence Models
Mon, 10/19 LSTMs pptx | pdf | pdf↓ video
Wed, 10/21 Machine translation; seq2seq pptx | pdf | pdf↓ video
Fri, 10/23 Attention; transformers pptx | pdf | pdf↓ video
Week 8 Sequence-to-Sequence Models, Deep Learning on Structured Data
Mon, 10/26 Transformers continued pptx | pdf | pdf↓ video
Wed, 10/28 Scaling deep learning systems
Sustainable deep learning
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Fri, 10/30 Deep learning on trees: Recursive neural nets (RvNNs) pptx | pdf | pdf↓ video
Week 9 Deep Learning on Structured Data, Reinforcement Learning
Mon, 11/2 Deep learning on graphs: Graph convolutional nets (GCNs) pptx | pdf | pdf↓ video
Wed, 11/4 Intro to RL pptx | pdf | pdf↓ video
Fri, 11/6 Rl intro continued; value iteration
Model interpretability
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Week 10 Reinforcement Learning Continued
Mon, 11/9 Tabular Q learning
Deep Q learning
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Wed, 11/11 Policy gradient methods, REINFORCE pptx | pdf | pdf↓ video
Fri, 11/13 Actor-critic methods pptx | pdf | pdf↓ video
Week 11 Unsupervised Learning
Mon, 11/16 RL conclusion pptx | pdf | pdf↓ video
Wed, 11/18 Autoencoders pptx | pdf | pdf↓ video
Fri, 11/20 GANs pptx | pdf | pdf↓ video
Week 12 Thanksgiving Week
Mon, 11/23 VAEs pptx | pdf | pdf↓ video
Wed, 11/25 No class (Thanksgiving 🦃🦃🦃)
Fri, 11/27 No class (Thanksgiving 🦃🦃🦃)
Week 13 Conclusion
Mon, 11/30 Deepfakes pptx | pdf | pdf↓ video
Wed, 12/2 [Slack day]
Fri, 12/4 [Slack day]
Week 14 Finals week
Mon, 12/7 No class
Wed, 12/9 No class
Fri, 12/11 Deep Learning Day! (Final project presentations / mini conference)