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Welcome to the website for Sta-395, Introduction to Machine Learning! To begin, you can find the course syllabus linked below:

You can locate course content by scrolling, or by using the navigation bar in the upper-left.

Course Materials

Most class meetings involve both lecture and lab components. Topics are organized into units, which can be found below. The assignments and due-dates for a given week can be found below that week’s course materials. Unless otherwise indicated, all assignments are to be submitted via Canvas by 11:59pm.

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Unit #1 - Concepts, Workflow, and Methods for Tabular Data

Week 0/1 - Introduction to Python and sklearn

Date Lecture Lab Resources
Th 8/28 Introduction Lab 1 - Crash Course in Python
T 9/2 KNN and Decision Trees Finish Lab 1
Th 9/4 Data Pre-processing Lab 2 - Introduction to sklearn
  • Lab 1 is due Monday 9/8 at 11:59pm on Canvas
  • Lab 2 is due Wednesday 9/10 at 11:59pm on Canvas

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Week 2 - Cross-validation and model comparisons

Date Lecture Lab Resources
T 9/9 Finish/discuss Lab 2
Th 9/11 Cross-validation Lab 3 - Pipelines and Cross-Validation
  • Homework 1 is due Friday 9/12 at 11:59pm on Canvas
  • Lab 3 is due Wednesday 9/17 at 11:59pm on Canvas

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Week 3 - Classifier performance

Date Lecture Lab Resources
T 9/16 Assessing classifier performance Finish/discuss Lab 3
Th 9/18 Lab 4 - Scoring Metrics
  • Homework 2 is due Monday 9/29 at 11:59pm on Canvas
  • Lab 4 is due Wednesday 9/24 at 11:59pm

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Week 4 - Regression and machine learning

Date Lecture Lab Resources
T 9/23 Feature Transformations and Expansions Finish/discuss Lab 4
Th 9/25 Regression for Classification Lab 5 - Regression and Machine Learning
  • Lab 5 is due Wednesday 10/1 at 11:59pm

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Week 5 - Regularization

Date Lecture Lab Resources
T 9/30 Regularization Finish/discuss Lab 5
Th 10/2 Lab 6 - Regularized Regression
  • Lab 6 is due Wednesday 10/8 at 11:59pm
  • Homework 3 is due Friday 10/17 at 11:59pm
    • Benchmark scores for this assignment will be released soon \(~\)

Week 6 - More Models

Date Lecture Lab Resources
T 10/7 Support Vector Machines Lab 7 - Support Vector Machines An Idiot’s Guide to SVMs
Th 10/9 Random Forest Lab 8 - Ensembles and Feature Engineering
  • Lab 7 is due Monday 10/14
  • Lab 8 is due Wednesday 10/16

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Week 7 - More Models (cont.)

Date Lecture Lab Resources
T 10/14 Gradient Boosting Lab 8 (cont.)
Th 10/16 Lab 9 - Gradient Boosting with xgboost
  • Lab 9 is due Friday 10/17

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Unit #2 - Mathematics and “Deep Learning”

Week 8 - Gradient Descent Algorithms

Date Lecture Lab Resources
T 10/28 Lab 10 - Linear Algebra Review
Th 10/30 Gradient Descent Algorithms
  • Lab 9 (from before break) is due Wednesday 10/29
  • Lab 10 is due Friday 10/31
  • Homework 4 is due Tuesday 11/11

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Week 9 - Neural Networks and Backpropogation

Date Lecture Lab Resources
T 11/4 Lab 11 - Gradient Descent Algorithms
Th 11/6 Neural Networks Finish/discuss Lab 11
  • Lab 11 is due Friday 11/7

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Week 10 - Neural Networks

Date Lecture Lab Resources
T 11/11 Lab 12 - Neural Networks in PyTorch
Th 11/13 Convolutional Neural Networks Lab 13 - Convolutional Neural Networks
  • Lab 12 is due Tuesday 11/18
  • Lab 13 will be due after the exam on date that is to be determined

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Week 11 - Exam Preparation

Date Lecture Lab Resources
T 11/18 Exam Review Finishing up previous labs
Th 11/20 Exam
  • Our exam is on Thursday 11/20. We will have a review session on Tuesday 11/18 and you will be able to retake up to 3 quizzes at the end of the review session.
  • Here is a practice exam. It is slightly shorter than the actual exam will be, but it should provide a good indication of the format and style of questions used in the actual exam.

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Week 12 - More Neural Networks

Date Lecture Lab Resources
T 11/25 Lab 14 - Transfer Learning
Th 11/27 No class - Thanksgiving
  • Lab 13 (CNNs) is due Wednesday 11/26

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Week 13

Date Lecture Lab Resources
T 12/2 Recurrent Neural Networks Lab 15 - RNNs (optional)
Th 12/4 Finish Labs 14, 15 and Project Prep
  • Lab 14 is due Friday 12/5
  • Lab 15 can be completed for extra credit and I’ll accept it any time before Friday

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Week 14

Date Lecture Lab Resources
T 12/9 Project Presentations #1
Th 12/11 Project Presentations #2

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Final Project

Final Project Description

  • The first project deadline is Tuesday 10/28 - one team member must indicate all members of your project team via email
  • The second project deadline is Friday 10/31 - one team member must share a short (1-2 paragraph) proposal via email describing your planned topic, including the data source.
  • During Week 13 (the week of Tuesday 12/2) each group is to share an informal, 3-5 minute progress briefing regarding the status of your project. You should be prepared to describe your research aims, data, and current progress. You do not need to prepare any materials or have any formal results yet.