Machine Learning Course Schedule
| Week | Learning Activities | Assignment |
|---|---|---|
| 1 | Course Overview Introduction to Python Introduction to Machine Learning Quick Draw TensorFlow Playground |
Install Python and Packages Begin Python (12 Modules) |
| 2 | Data Engineering (Part 1) Gather Data Statistics and Math Review Visualize Data Cleanse Data |
Data Science with TCLab (1-4) Introduction TCLab Help 1. Overview 2. Import Data 3. Statistics 4. Visualize |
| 3 | Data Engineering (Part 2) Feature Engineering Imbalanced Data Scale Data Split Data |
Data Science with TCLab (5-8) 5. Prepare Data 6. Regression 7. Features 8. Classification |
| 4 | Regression Linear Regression k-Nearest Neighbors Neural Network Regressor Support Vector Regressor XGBoost Regressor Case Study: Steel Plate Faults |
k-Nearest Neighbors Regression Case Study Polymer Melt Flow Rate |
| 5 |
Classification Case Study: Concrete Strength Convolutional Neural Network |
Logistic Regression Classification Case Study Sonar Detection |
| 6 | Mid-Term Exam Review |
Mid-Term Exam Additive Manufacturing |
| Week | Learning Activities | Assignment |
|---|---|---|
| 7 | Solve Equations KKT Conditions Differential Equations Time Series and MPC |
Data Science with TCLab (9-12) 9. Interpolation 10. Solve Equations 11. Differential Equations 12. Time Series |
| 8 | Data Engineering (Part 3) Deploy Machine Learning LSTM Networks |
Replace PID with LSTM Automation |
| 9 | Steel Plate Performance Metrics |
Hybrid Machine Learning Thermo Properties |
| 10 | Computer Vision Introduction Cascade Classifier Deep Learning Classification |
Road Detection Texture Classification |
| 11 | Final Exam Review |
Final Exam Individual: Wind Power Group: Facial Recognition |
| Week | Learning Activities | Assignment |
|---|---|---|
| 12 | Course Project |
Course Project Proposal Progress Report #1: Data Visualization, Exploration, and Cleansing |
| 13 | Course Project |
Progress Report #2: Regression, Classification, Clustering, Dimensionality Reduction
Progress Report #3: Optimize Hyperparameters, Validation, Deployment Performance |
| 14 | Course Project | Final Project Report and Presentation |
