COMS W4995 Applied Machine Learning Spring 2020 - Schedule

Press P on slides for presenter notes (or add #p1 to the url if you’re on mobile or click on ).

# Date Topic Reading Comments
1 Wed 01/22/20 Introduction   IMLP Ch 1, APM Ch 1-2
2 Mon 01/27/20 matplotlib and visualization   Fundamentals of Data Visualization, Systematising Glyph Design for Visualization (Chapter 2) HW 1 posted

Wed 01/29/20 No class
3 Mon 02/03/20 Supervised learning, model complexity and model validation   IMLP Ch2.1-2.3.2, APM Ch 4-4.3, IMLP Ch 5.1, 5.2, APM Ch 4.4-4.8
4
 Wed 02/05/20 Preprocessing   IMLP Ch 3.3, IMLP Ch 4.1-4.6, APM Ch 3, HW 1 due, HW 2 posted
5 Mon 02/10/20 Linear models for Regression   IMLP p45-68, APM Ch 6
6 Wed 02/12/20 Linear models for Classification, SVMs  
7 Mon 02/17/20 Trees, Forests & Ensembles   IMLP 2.3.5, 2.3.6, APM Ch 14.1-14.4
8
 Wed 02/19/20 Gradient Descent, Gradient Boosting   IMLP 2.3.6, APM Ch 14.5 HW 2 due
9 Mon 02/24/20 Model Evaluation   IMLP 5.3, APM Ch 16 HW 3 posted
Wed 02/26/20 No class
10 Mon 03/02/20 Calibration, Imbalanced Data   APM Ch16, SMOTE, Easy Ensembles
11 Wed 03/04/20 Model Interpretration and Feature Selection   Interpretable Machine Learning, Limitations of Interpretable Machine Learning
Mon 03/09/20 Class cancelled

Wed 03/11/20 Midterm

Mon 03/16/20 Spring break


Wed 03/18/20 Spring break

Mon 03/23/20 Class suspended

Wed 03/25/20 Class suspended

12 Mon 03/30/20 Parameter tuning and Automatic Machine Learning   AutoML book (chapter 1 gives a great intro), NeurIPS tutorial video
13 Wed 04/01/20 Dimensionality Reduction   IMLP Ch 3.4.1, 3.4.3, APM p35-40 HW 3 due
14 Mon 04/06/20 Clustering and mixture models   IMLP 3.5
15 Wed 04/08/20 Working with text data   IMLP Ch 7.1-7.8
16 Mon 04/13/20 Topic models for text data   IMLP Ch 7.9, Tim Hopper, Understanding Topic Models HW 4 posted
19 Wed 04/15/20 Word and document embeddings Mikolov 2013a, Mikolov 2013b, gensim word2vec
18 Mon 04/20/20 Neural Networks IMLP Ch 2.3.8, DL Ch 6, Ch 7.8
19 Wed 04/22/20 Keras and Convolutional Neural Nets DL Ch 7.12, Ch 9, keras docs, Stanford CNN course notes, Module 2, Feature Visualization HW 4 due, HW 5 posted
20 Mon 04/27/20 Advanced Neural Networks
21 Wed 04/29/20 Time series data   HW 5 due
Mon 05/04/20 Second Exam


IMLP: Mueller, Guido - Introduction to machine learning with python
APM: Kuhn, Johnson - Applied predictive modeling
DL: Goodfellow, Bengio, Courville - Deep Learning