YuchenUofTnotes
This collection of notes aims to help myself learn Math & Stats efficiently. Since one course gives dozens of theorems and corollaries, sorting them into clean notes is usually a good way to include them in the knowledge network in my mind.
🖋 Complete Notes

🗝 STA447 Stochastic Processes (Winter 2020)

🗝 STA414 Statistical Methods for Machine Learning II (Winter 2020)

🗝 MAT337 Real Analysis (Winter 2020)

🗝 APM462 Nonlinear Optimizations (Fall 2019)

🗝 STA347 Probability I (Fall 2019)

🗝 STA302 Methods of Data Analysis (Summer 2019)

🗝 MAT224 Linear Algebra II (Winter 2019)

🗝 MAT237 Advanced Calculus (Fall 2018 & Winter 2019), Made together with @tingfengx
 With special comments about kdimensional manifolds, which is more abstract than materials covered in lecture.
🗃 Archived Notes
 🎓 CSC418 Computer Graphics (Summer 2020)
 Raster Images
 Ray Casting
 Ray Tracing
 Bounding Volume Hierachy
 Triangle Meshes
 Shader Pipeline
 MassSpring Systems
 🎓 CSC413 Neural Networks and Deep Learning (Winter 2020)
 Introduction & Linear Models
 Multilayer Perceptrons & Backpropagation
 Automatic Differentiation & Distributed Representations
 Optimization
 Convolutional Neural Networks & Image Classification
 🎓 CSC311 Introduction to Machine Learning (Fall 2019)
 kMeans and EM Algorithm
 Reinforcement Learning
 🎓 STA261 (Winter 2019)
 Converge in distribution
 Normal Distribution Theory
 Expectation and Covariance
 Different Types of Estimation
 Sampling Distributions
 Consistent & Efficient Estimators
 🎓 CSC263 Data Structures and Analysis (Winter 2019)
 Some notes on AVL trees
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