HOML = Hands-On Machine Learning
| Class # | Date | Topic | Reading | Assignment | Due |
| 1 | Tue, Jan 16 | Class Introduction Taxonomy of Machine Learning Methods | Syllabus HOML CH 1 | ||
| 2 | Thu, Jan 18 | Introduction to Scikit-Learn and Pandas | HOML CH 2 | ||
| 3 | Tue, Jan 23 | Introduction cont Classifiers | HOML CH 3 | ||
| 4 | Thu, Jan 25 | Nonlinear Regression | HOML CH 4.1-4.4 | ||
| 5 | Tue, Jan 30 | Regularization and Logistic Regression | HOML CH 4.5-4.6 | HW 1 | |
| 6 | Thu, Feb 1 | Support Vector Machines | HOML CH 5 | ||
| 7 | Tue, Feb 6 | Decision Trees: Basics | HOML CH 6 | HW 1 | |
| 8 | Thu, Feb 8 | Decision Trees: Ensemble Methods | HOML CH 7.1-7.3 | HW 2 | |
| 9 | Tue, Feb 13 | Decision Trees: Random Forests | HOML CH 7.4-7.6 | ||
| 10 | Thu, Feb 15 | Nonlinear Dimensionality Reduction: PCA and Kernel PCA | HOML CH 8.1-8.4 | HW 2 | |
| 11 | Tue, Feb 20 | Nonlinear Dimensionality Reduction: LLE and ISOmap | HOML CH 8.5-8.6 | HW 3 | |
| 12 | Thu, Feb 22 | Semi-Supervised Learning | TBD | ||
| 13 | Tue, Feb 27 | Feedforward Neural Network Basics | HOML Ch 10.1 | HW 3 | |
| 14 | Thu, Mar 1 | Tensorflow Introduction | HOML Ch 9 | HW 4 | |
| 15 | Tue, Mar 6 | Feedforward Neural Networks in TensorFlow | HOML Ch 10.2-10.4 | ||
| 16 | Thu, Mar 8 | Deep Neural Networks: Gradient Problems and Pretrained Layers | HOML CH 11.1-11.2 | HW 4 | |
| 17 | Tue, Mar 13 | Deep Neural Networks: Optimization and Regularization | HOML CH 11.3-11.5 | HW 5 | |
| 18 | Thu, Mar 15 | Distributed Tensorflow | HOML CH 12 | ||
| - | Tue, Mar 20 | Holiday | |||
| - | Thu, Mar 22 | Holiday | |||
| 19 | Tue, Mar 27 | Convolutional Neural Networks: Convolution | HOML CH 13.1-13.2 | HW 5 | |
| 20 | Thu, Mar 29 | Convolutional Neural Networks: Pooling and Architectures | HOML CH 13.3-13.4 | HW 6 | |
| 21 | Tue, Apr 3 | Recurrent Neural Networks: Design and Training | HOML CH 14.1-14.3 | ||
| 22 | Thu, Apr 5 | Recurrent Neural Networks: Deep Learning and Examples | HOML CH 14.4-14.7 | HW 6 | |
| 23 | Tue, Apr 10 | Project Proposals | n/a | Presentation | |
| 24 | Thu, Apr 12 | Autoencoders: Basics and Unsupervised Training | HOML CH 15.1-15.4 | ||
| 25 | Tue, Apr 17 | Autoencoders: Variations | HOML CH 15.5-15.8 | ||
| 26 | Thu, Apr 19 | Case Study: Convolutional Nns and Image Understanding | TBD | ||
| 27 | Tue, Apr 24 | Case Study: Recurrent Neural Networks and Brain-Machine Interfaces | TBD | ||
| 28 | Thu, Apr 26 | Project Checkpoint | n/a | Presentation | |
| 29 | Tue, May 1 | Case Study: Recurrent Neural Networks and Modeling Dynamcis | TBD | ||
| 30 | Thu, May 3 | Case Study: Recurrent Neural Networks and Short-Term Memory | TBD | ||
| 31 | Fri, May 4 | Final Project Presentations (Poster Session) | Final Projects | ||
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