Syllabus week! Tips for success.

**Dates:**Monday, January 13 - Friday, January 17**Reading:**STAT 432 Syllabus**Reading:**Ten Simple Rules for Success in STAT 432

Machine learning tasks. Probability and statistics review. Computing tips, tricks, and resources.

**Dates:**Monday, January 20 - Friday, January 24**Office Hours:**Wednesday, 4:00 PM - 7:00 PM, 1306 Everitt Laboratory**Video:**Welcome!**Reading:**Machine Learning Overview**Reading:**Computing**Reading:**Probability**Reading:**Statistics**Assignment:**Quiz 01

Introduction to supervised learning. Using linear regression for prediction. Estimating conditional means. Using `lm()`

. Metrics for regression tasks. Data splits for model evaluation.

**Dates:**Monday, January 27 - Friday, January 31**(Main) Office Hours:**Wednesday, 4:00 PM - 7:00 PM, 1306 Everitt Laboratory**(CA) Office Hours:**Thursday, 3:00 PM - 5:00 PM, 108 English Building**Video:**Week 02 Logistics**Video:**Linear Regression R Tutorial**Reading:**Probability**Reading:**Statistics**Reading:**Linear Regression**Assignment:**Quiz 02**Assignment:**Exam 00A

k-nearest neighbors. Decision trees. Parametric versus nonparametric models. Using Categorical features and interactions.

**Dates:**Monday, February 3 - Friday, February 7**(Main) Office Hours:**Wednesday, 4:00 PM - 7:00 PM, 1306 Everitt Laboratory**(CA) Office Hours:**Thursday, 3:00 PM - 5:00 PM, 108 English Building**Video:**Nonparametric Regression**Reading:**Nonparametric Regression**Assignment:**Quiz 03**Assignment:**Exam 00B

Bias-variane tradeoff. Regression overview.

**Dates:**Monday, February 10 - Friday, February 14**(Main) Office Hours:**Wednesday, 4:00 PM - 7:00 PM, 1306 Everitt Laboratory**(CA) Office Hours:**Thursday, 3:00 PM - 5:00 PM, 108 English Building**Video:**Regression Model Flexibility**Video:**The`map()`

Function**Reading:**Bias–Variance Tradeoff**Reading:**Regression Overview**Assignment:**Quiz 04

Introduction to classification. Probability models and the Bayes Classifier. k-nearest neighbors and decision trees again.

**Dates:**Monday, February 17 - Friday, February 21**(Main) Office Hours:**Wednesday, 4:00 PM - 7:00 PM, 1306 Everitt Laboratory**(CA) Office Hours:**Thursday, 3:00 PM - 5:00 PM, 108 English Building**Video:**Classification**Slides:**Classification**Assignment:**Quiz 05

Exam week!

**Dates:**Monday, February 24 - Friday, February 28**Assignment:**Exam 01**Assignment:**Graduate Quiz 01

Specifics and metrics for binary classification. Logistic regression.

**Dates:**Monday, March 2 - Friday, March 6**Assignment:**Quiz 06

Generative versus discriminative models. LDA, QDA, and Naive Bayes.

**Dates:**Monday, March 9 - Friday, March 13**Assignment:**Quiz 07

Resampling methods. Model tuning using cross-validation.

**Dates:**Monday, March 23 - Friday, March 27**Assignment:**Quiz 08

Regularization with ridge and lasso. Deimension reduction.

**Dates:**Monday, March 30 - Friday, April 3**Assignment:**Quiz 09

Ensemble methods. Bagging, random forest, and boosting.

**Dates:**Monday, April 6 - Friday, April 10**Assignment:**Quiz 10

Exam week!

**Dates:**Monday, April 13 - Friday, April 17**Assignment:**Exam 02**Assignment:**Graduate Quiz 02**Assignment:**Analysis 00

Using machine learning for data analysis.

**Dates:**Monday, April 20 - Friday, April 24**Assignment:**Analysis 01**Assignment:**Analysis 01 Quiz

Some quick thoughts on unsupervised learning.

**Dates:**Monday, April 27 - Friday, May 1**Assignment:**Analysis 01 Reflection**Assignment:**Analysis 02**Assignment:**Analysis 02 Quiz

Work on analyses!

**Dates:**Monday, May 4 - Friday, May 8**Assignment:**Analysis 02 Reflection**Assignment:**Analysis 03**Assignment:**Analysis 03 Quiz

Assignment | Deadline | Deadline Day | System |
---|---|---|---|

Quiz 01 | 24-Jan | Friday | PrairieLearn |

Quiz 02 | 31-Jan | Friday | PrairieLearn |

Exam 00A | 2-Feb | Sunday | CBTF |

Quiz 03 | 7-Feb | Friday | PrairieLearn |

Exam 00B | 7-Feb | Friday | CBTF |

Quiz 04 | 14-Feb | Friday | PrairieLearn |

Quiz 05 | 21-Feb | Friday | PrairieLearn |

Exam 01 | 28-Feb | Friday | CBTF |

Graduate Quiz 01 | 28-Feb | Friday | PrairieLearn |

Quiz 06 | 6-Mar | Friday | PrairieLearn |

Quiz 07 | 13-Mar | Friday | PrairieLearn |

Quiz 08 | 27-Mar | Friday | PrairieLearn |

Quiz 09 | 3-Apr | Friday | PrairieLearn |

Quiz 10 | 10-Apr | Friday | PrairieLearn |

Exam 02 | 17-Apr | Friday | CBTF |

Graduate Quiz 02 | 17-Apr | Friday | PrairieLearn |

Analysis 01 IMRAD | 24-Apr | Friday | Canvas |

Analysis 01 Code | 24-Apr | Friday | Canvas |

Analysis 01 Quiz | 24-Apr | Friday | PrairieLearn |

Analysis 01 Reflection | 1-May | Friday | Canvas |

Analysis 02 IMRAD | 1-May | Friday | Canvas |

Analysis 02 Code | 1-May | Friday | Canvas |

Analysis 02 Quiz | 1-May | Friday | PrairieLearn |

Analysis 02 Reflection | 8-May | Friday | Canvas |

Analysis 03 IMRAD | 8-May | Friday | Canvas |

Analysis 03 Code | 8-May | Friday | Canvas |

Analysis 03 Quiz | 8-May | Friday | PrairieLearn |

Analysis 03 Reflection | 12-May | Tuesday | Canvas |