Tomodachii
Homepage
Categories
6.041SC Probabilistic Systems Analysis and Applied Probability by
John N. Tsitsiklis
- Lecture 5 + 6 + 7: Discrete Random Variables (
Mar 31, 2025
)
- Lecture 5 + 6 + 7: Discrete Random Variables - Examples and Exercises (
Mar 31, 2025
)
- Lecture 8: Continuous Random Variables (
Mar 17, 2025
)
- Lecture 9 + 10: Joint Distribution, Conditioning and Independence (
Apr 19, 2025
)
Computers and Intractability: A Guide to the Theory of NP-Completeness by
Michael R. Garey
,
David S. Johnson
- Chapter 1: Computers, Complexity and Intractability (
Apr 2, 2025
)
CS109: Probability for Computer Scientists by
Chris Piech
- Lecture 21: MLE (
Apr 7, 2025
)
Density Estimation for Statistics and Data Analysis by
B.W. Silverman
- Master Note (
Apr 4, 2025
)
- Chapter 1 + 2: Introduction and Survey of existing methods (
Apr 3, 2025
)
- Chapter 3: The kernel method for univariate data (
Apr 3, 2025
)
Gaussian Processes for Machine Learning by
Carl Edward Rasmussen
,
Christopher K. I. Williams
- Preface (
Mar 17, 2025
)
- Chapter 2: Regression (
Mar 17, 2025
)
Introduction to Causal Inference from a Machine Learning Perspective by
Brady Neal
- Lecture 1: Motivation (
Apr 16, 2025
)
Probabilistic Graphical Models by
Daphne Koller
,
Nir Friedman
- Chapter 1 + 2: Introduction and Foundations (
Mar 19, 2025
)
- Chapter 3: The Bayesian Network Representation (
Mar 19, 2025
)
- Chapter 4 Undirected Graphical Models (
Apr 9, 2025
)
- Chapter 5: Local Probabilistic Models (
Mar 28, 2025
)
- Chapter 9: Exact Inference - Variable Elimination (
Apr 3, 2025
)
- Chapter 10 Exact Inference Clique Trees (
Apr 18, 2025
)
- Chapter 16: Learning Graphical Models - Overview (
Apr 15, 2025
)
- Chapter 17: Parameter Estimation (
Apr 15, 2025
)
Probabilistic Machine Learning: An Introduction by
Kevin P. Murphy
- Chapter 2: Probability - Univariate Models (
Apr 6, 2025
)
Random by
Tomodachii
- Insertion Sort (
Jul 24, 2024
)