math3480

Math 3480 - Machine Learning - Snow College

These are the lecture notes I will use for class in our Machine Learning Course at Snow College. As I make changes, I will update these notes here on github.

You are welcome to keep a copy of these notes for your own reference after class.

If you have any questions, or if you note any problems with these notes, feel free to let me know and I can take a look. Have fun this semester!

Dr. Michael E. Olson
Science Building, Rm. 312
Snow College

Machine Learning

• Machine Learning Demo
• Types of Machine Learning
• Preprocessing (Data Cleaning and Data Wrangling)
  • Feature Engineering
• Review of EDA (Exploratory Data Analysis)
• Cross Validation and Feature Scaling

Regression Models

• Regression and Evaluation of Regression Models
  • Linear Regression (from MATH 3080)
• Polynomial Regression
• Ridge and Lasso Regression

Classification Models

• Classification and Evaluation of Classification Models
  • k-Nearest Neighbors (from MATH 3080)
  • Logistic Regression (from MATH 3280)
• Naive Bayes
• Support Vector Machines
• Neural Networks
• Decision Trees
  • Ensemble Models
  • Random Forests

Clustering Models

• Clustering and Evaluation of Clustering Models
  • KMeans (from MATH 3080)
• Gaussian Mixture Models
• Hierarchical Clustering
• DBSCAN

Natural Language Processing

• Overview of Natural Language Processing
• Bag of Words modeling
• n-grams
• Grammars