DSC 340: Machine Learning and Neural Networks
Week 1: Introduction to Machine Learning
- Slides
- Lecture Notes
- Pre-Class Assignment
- Data Set
- In-Class Assignment
- Post-Class Assignment
Week 2: Linear Regression and the Machine Learning Workflow
Week 3: Regularized Linear Models
Week 4: Using Machine Learning to Solve Classification Problems
Week 5: Model Optimization and Nonlinear Models
- Slides
- Lecture Notes
- [Pre-Class Assignment]
- In-Class Assignment
- Post-Class Assignment
Week 6: Unsupervised Machine Learning: Clustering and Dimensionality Reduction
Week 7: Introduction to Neural Networks
- Slides
- Lecture Notes
- Pre-Class Assignment
- In-Class Assignment
- Post-Class Assignment
Week 8: Creating Neural Networks with Tensorflow
Week 9: Creating Neural Networks from Scratch
- Slides
- Lecture Notes
- Pre-Class Assignment
- Data Set
- In-Class and Post-Class Assignments
Week 10: Introduction to Convolutional Neural Networks
- Slides
- Lecture Notes
- Pre-Class Assignment
- In-Class Assignment
- Post-Class Assignment
Week 11: Advanced Methods for Improving the Performance of Convolutional Neural Networks
- Slides
- Lecture Notes
- Pre-Class Assignment
- In-Class Assignment
- Post-Class Assignment
Week 12: Recurrent Neural Networks
- Slides
- Lecture Notes
- Pre-Class Assignment
- In-Class Assignment
- Post-Class Assignment
Week 13: Large Language Models
- Slides
- Lecture Notes
- Pre-Class Assignment
- In-Class Assignment
- Post-Class Assignment