Schedule

Week Date Topic Reading Comments
1 01/18/17 Introduction; What can machine learning do for you? IMLP Ch 1, APM Ch 1-2
2 01/23/17 Python, git, github, testing, CI, documentation IMLP Ch 1, git video Homework 1 posted

01/25/17 matplotlib and visualization colormap talk
3 01/30/17 Introduction to supervised learning, basic model selection IMLP p25-44, APM Ch 4-4.3, IMLP p251-262, APM Ch 4.4-4.8

02/01/17 Linear models for Regression IMLP p45-68, APM Ch 6
4 02/06/17 Linear models for Classification IMLP p45-68, Ch 12.1-12.2, 12.5

02/08/17 Preprocessing and feature engineering IMLP p132-140, IMLP p211-220, APM Ch 3 Homework 1 due
5 02/13/17 Imputation and Feature Selection IMLP p236-241, APM Ch 19 Homework 2 posted

02/15/17 Support Vector Machines for Classification and Regression IMLP p92-103, APM Ch 13.4
6 02/20/17 Decision Trees and Random Forests IMLP p70-88, APM Ch 14.1-14.4

02/22/17 Gradient Boosting, Calibration IMLP p89-92, APM Ch 14.5
7 02/27/17 Model evaluation and imbalanced datasets IMLP p275-302, APM Ch 16 Homework 2 due

03/01/17 Case Studies (bring laptop)
8 03/06/17 PCA, Discriminant Analysis, Manifold Learning

03/08/17 Midterm

9 03/13/17 Spring break


03/15/17 Spring break

10 03/20/17 Resampling strategies for Imbalanced Data
APM Ch16, SMOTE, Easy Ensembles Homework 3 posted

03/22/17 Clustering and mixture models
IMLP p168-208
11 03/27/17 Data decomposition and dimensionality reduction IMLP p140-168

03/29/17 Outlier Detection
12 04/03/17 Working with text data IMLP p323-336 Homework 3 due, Homework 4 posted

04/05/17 Topic models for text data IMLP p347-355
13 04/10/17 Neural Networks with Tensorflow
Homework 4 due

04/12/17 Learning and tuning neural networks

14 04/17/17 Convolutional neural networks for image classification
Homework 5 posted

04/19/17 Working with time-series data

15 04/24/17 Models for time series data


04/26/17 Machine Learning in Production IMLP Ch 8, HICC Homework 5 due
16 05/01/17 Second Exam


IMLP: Mueller, Guido - Introduction to machine learning with python
APM: Kuhn, Johnson - Applied predictive modeling