CS82: Statistical Learning
Prerequisites: Completion of CS01b or AP CS, or permission of instructor. Also requires Algebra II math experience.
CS82 is the most math heavy course offered at KTBYTE, and require students to have mastered self-guided learning. Students will learn tools to model and understand complex data sets, tools and algorithms that are commonly used for tackling "Big Data" problems. Covered concepts include descriptive statistics, linear/logistic regression, basic probability, clustering, naive bayes, q-learning, sk-learn libraries, and more. Unlike our other courses, this one is taught in Python.
- Data Formats
- Descriptive Statistics
- Linear Regression
- Basis Functions
- Common problems with linear models
- Shrinkage, Ridge Regression
- Cross Validation, Dimensionality Reduction
- Classification: Logistic Regression
- Old Homework Assignments