Additional Resources
This page contains additional resources for each lecture to help you dive deeper into the topics covered.
Introduction to Programming in Python
Data Structures
Introduction to SWE I
Coming soon…
Introduction to SWE II
Coming soon…
Databases
Coming soon…
Linear Algebra for ML
- EECS 16A fa22 notes - System of Linear Equations
- EECS 16A fa22 notes - Matrices and Vectors
- EECS 16A fa22 notes - Matrix Multiplication
- EECS 16A sp25 notes - Vector Spaces, Subspaces, Bases
- EECS 16A sp25 notes - Linear (In)dependence
- EECS 16A sp25 notes - Four Fundamental Subspaces, Rank-Nullity Theorem
- EECS 16a sp25 notes - Matrix Diagonalization and Change of Basis
- EECS 16a fa22 notes - Least Squares
- EECS 16A sp25 notes - Spectral Theorem
- EECS 16A sp25 notes - SVD
- EECS 16A sp25 notes - Low Rank Approximation
Calculus for ML
- EECS 127 sp24 Reader - Vector Calculus
- EECS 127 sp24 - Vector Calculus I Recording - Watch until end
- EECS 127 sp24 - Vector Calculus II Recording - Watch until 34:45
- MATH 53 fa22 notes - Directional Derivatives and the Gradient Vector
- MATH 53 fa22 notes - Partial Derivatives, Tangent Planes, and Linear Approximations
- MATH 53 fa22 notes - The Chain Rule
Probability for ML
Coming soon…
Classical ML
Coming soon…