Prerequisites:Calculus, Linear Algebra, Probabilities and Stats

Answering the following questions will tell you if you are ready to take the Machine Learning class. If you are not able to answer “Yes” to these questions, then we suggest that you go through the reading list at the end of this page.

• Do you know matrix multiplication?
• Do you know what are eigenvectors? Do you know how to calculate eigenvalues of a matrix?
• Can you decompose a matrix using SVD (Singular Value Decomposition)?
• Do you know what are the conditions of a valid distance metric?
• Do you know what is the Bayes Rule?
• Can you calculate the expectation of a random variable?
• Can you calculate the covariance/correlation between two random variables?
• Do you know gradient or slope?
• Are you familiar with chain rule in calculus?
• Have you worked (not necessarily programmed) with a Python, R, Matlab or Java program?

Reading List

• Khan Academy's introduction to vectors
• Khan Academy's introduction to matrices
• Linear Algebra Review and Reference PDF
• Review of Probability Theory PDF

Free Online Stanford Machine Learning Course by Andrew Ng

• Machine Learning by Professor Andrew Ng Click