| Date | Day | Topic | Slides |
|---|---|---|---|
| 20-Jan | Tue | Logistics, Introduction to IPython notebooks, Scientific Python and Socrative | [PDF] |
| 22-Jan | Thu | Introduction to Data Visualization | [PDF] |
| 27-Jan | Tue | Principles of Data Visualization | [PDF] |
| 29-Jan | Thu | Data Collection and Munging |
[PDF]
[IPynb]
[FB Scraping Code] |
| 3-Feb | Tue | Exploratory Data Analysis | [IPynb] |
| 5-Feb | Thu | Intro to Classification, Nearest Neighbor classifier | [PDF] |
| 10-Feb | Tue | Decision Trees | [PDF] |
| 12-Feb | Thu | Linear Regression, Regression Trees | [PDF] |
| 17-Feb | Tue | Probabilistic Classifiers, Naive Bayes, SVM and Kernels | [PDF] |
| 19-Feb | Thu | Catchup | |
| 24-Feb | Tue | UTA Closed due to Snow! | |
| 26-Feb | Thu | Model Evaluation | [PDF] |
| 3-Mar | Tue | K-Means Clustering | [PPT] |
| 5-Mar | Thu | UTA Closed due to Snow! | |
| 10-Mar | Tue | No Class - Spring Break | |
| 12-Mar | Thu | No Class - Spring Break | |
| 17-Mar | Tue | Hierarchical Clustering | Same as K-Means |
| 19-Mar | Thu | Frequent Itemsets and Association Rule Mining | [PPT] |
| 24-Mar | Tue | Midterm | |
| 26-Mar | Thu | Search Engine Basics: Answering Keyword queries | [PDF] |
| 31-Mar | Tue | Search Engine Basics: Link Analysis | [PDF1] [PDF2] |
| 2-Apr | Thu | Search Engine Basics: Computational Advertising | [PDF] |
| 7-Apr | Tue | Recommender Systems I: Collaborative Filtering | [PDF] |
| 9-Apr | Thu | Recommender Systems II: Matrix Factorization based approaches, RecSys in Netflix | Same as above |
| 14-Apr | Tue | Dimensionality Reduction: PCA, LSH | [PDF] |
| 16-Apr | Thu | Ensemble Learning: Bagging (Random Forest), Boosting (AdaBoost, Boosted Decision trees) | [PDF] |
| 21-Apr | Tue | Feature Selection, Model Comparison | [PDF] |
| 23-Apr | Thu | Neural Networks | [PDF] |
| 24-Apr | Fri | Deep Learning | [ConvNets PDF] [PDF] |
| 28-Apr | Tue | Sampling, Resampling and Bootstrapping, Monte Carlo simulations | [PDF] |
| 30-Apr | Thu | Modern Data Mining Software Stack: MapReduce | [PDF] |
| 5-May | Tue | Model testing on Web - A/B, Bucket testing, Hypothesis testing | [PDF] [SlideShare] |
| 7-May | Thu | Data Mining: Tips and Tricks | |
| 12-May | Tue | Final Exam, 2-4:30 PM |