notebook · javid's blog · est. 2026

~ teaching notes & posts ~

Blog & Notes

Notes from teaching Yale's SD&S 365/565 with Prof. John Lafferty and CPSC 481/581 with Prof. Andre Wibisono. If you have ideas to enhance the content, reach out.

§ 01

machine learning notes

Sequence Models & Recurrent Neural Networks

Apr 10, 2022 · CS/Yale

Reinforcement Learning

Apr 1, 2022 · CS/Yale

Sparsity and Graphs

Mar 28, 2022 · CS/Yale

Variational Inference

Mar 11, 2022 · CS/Yale

Approximation Inference

Mar 7, 2022 · CS/Yale

Mar 2, 2022 · CS/Yale

Dirichlet Processes

Mar 2, 2022 · CS/Yale

Bayesian Inference

Feb 19, 2022 · CS/Yale

Neural Tangent Kernels

Feb 19, 2022 · CS/Yale

Representer Theorem

Feb 2022 · CS/Yale

Mercer's Theorem

Jan 16, 2022 · CS/Yale

Sparsity Meets Convexity

Jan 16, 2022 · CS/Yale

Expectation Maximization

Dec 6, 2021 · CS/Yale

Managing Large Brain Imaging Experiments

Dec 5, 2021 · CS/Yale

Mixture Models and EM

Dec 3, 2021 · CS/Yale

Posterior Inference

Nov 26, 2021 · CS/Yale

Empirical Risk Minimization

Nov 16, 2021 · CS/Yale

MLE and MAP Estimation

Nov 16, 2021 · CS/Yale

Stochastic Functions in Python

Nov 1, 2021 · CS/Yale

Oct 20, 2021 · CS/Yale

Optimal Transport

2021 · CS/Yale

Optimal Transport & Convexity

2021 · CS/Yale