Exam Topics

The following topics may be tested in the CSE 40 Testout Exam.

Basic Machine Learning Concepts and Definitions:

• Inductive reasoning

• Concept learning

• Machine learning as optimization problem

• Input/Output

• Hypothesis classes

• Error Types

• Overfitting and Underfitting

Basic Probability and Combinatorics: 

• Definitions

• Joint distributions, Marginal Distributions, Conditional Probability

• Sum Rule, Product Rule, Bayes Rule

• Counting, Combinations, Permutations 

Correlation vs. Causation: 

• Independence and Conditional Independence 

• Correlation vs. Causation 

• Confounding variables

Basic Linear Algebra and Optimization: 

• Vector and Matrix operations

• Convex and Non-Convex Optimization

• Gradient Descent 

Data Wrangling and Cleaning

• Data formatting and standardization

• Handling missing data

• Dealing with outliers

Basic Machine Learning Models: 

• Linear Models 

• Decision Trees 

• Nearest Neighbor 

Python, Pandas and SKLearn

• Ability to read, interpret and debug simple machine learning programs written in Python using Pandas and SKLearn