CSCI 4050U
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Part II: Neural Networks
Introduction
Part I: Prerequisites
Introduction
☑ Numpy
☑ Vectorized computation
☑ Masking and aggregation
☑ Plotting
☑ Linear Algebra
☑ Lines and Planes
☑ Calculus
☑ Optimization
☑ PyTorch
Part II: Neural Networks
Introduction
☑ Regression
☑ Logistic Regression
☑ Multi-layer Perceptron
☑ Backpropagation
Part III: Machine Learning Workflow
Introduction
☑ Training
☑ Evaluation
Part IV: Images
Introduction
☑ Image Representations
☑ Convolution and Pooling
☑ Convolutional Networks
☑ Residual Networks
Part V: Sequences
Introduction
👉 Sequence Processing
👉 Text Processing With Embedding
☐ Learning From Text Using RNN
☐ Long-Short Term Memory RNN
☐ Learning From Text Using LSTM
☒ Deep RNN
☒ Encoder Decoder Networks
☒ Sequence Generation
Part VI: ☒ Advanced topics
Introduction
Author
Ken Pu
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Title
Author
Title
Author
☑ Regression
Ken Pu
☑ Logistic Regression
Ken Pu
☑ Multi-layer Perceptron
Ken Pu
☑ Backpropagation
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