chrispiech / probabilityForComputerScientistsLinks
☆139Updated last year
Alternatives and similar repositories for probabilityForComputerScientists
Users that are interested in probabilityForComputerScientists are comparing it to the libraries listed below
Sorting:
- ML algorithms in depth☆272Updated last year
- NYU Artificial Intelligence Spring 2024☆61Updated last year
- ☆273Updated 7 months ago
- Inside Deep Learning: The math, the algorithms, the models☆274Updated 2 years ago
- This is a companion to the ‘Mathematical Foundations’ section of the book, Mathematics for Machine Learning by Marc Deisenroth, Aldo Fais…☆300Updated 5 years ago
- ☆91Updated 2 years ago
- Data Structures and Information Retrieval in Python☆135Updated last year
- NUS CS5242 Neural Networks and Deep Learning, Xavier Bresson, 2025☆408Updated 9 months ago
- Sources for the book "Machine Learning in Production"☆138Updated 6 months ago
- Notes on mathematical topics that pertain to machine learning☆113Updated 4 years ago
- ☆230Updated 4 months ago
- ☆211Updated 3 years ago
- Collection of my assignments and work in the class MATH51 at Stanford☆110Updated 11 years ago
- Interactive textbook on state-space models☆202Updated 2 years ago
- A collection of awesome mathematics and computer science courses☆139Updated last year
- Source code for the book "Math for Deep Learning" (No Starch Press)☆176Updated 10 months ago
- Probability - The Science of Uncertainty and Data☆123Updated 7 years ago
- Official Github for Wharton STAT 4830☆55Updated last week
- Python code (in the form of Jupyter ipython notebooks) to support the book "Math and Architectures of Deep Learning" (Krishnendu Chaudhur…☆243Updated last year
- This is the corresponding code for the book Transformers in Action☆124Updated 3 months ago
- Jupyter notebooks with exercises for the No bullshit guide to linear algebra.☆244Updated 3 months ago
- ☆77Updated last year
- This is the official repository for the book Transformers - The Definitive Guide☆74Updated last month
- ☆30Updated last year
- 🌀 Stanford CS 228 - Probabilistic Graphical Models☆92Updated 7 years ago
- ☆132Updated 2 years ago
- Python and MATLAB code for linear algebra textbook.☆209Updated 2 weeks ago
- Solutions to the exercises in Grinstead and Snell's Introduction to Probability☆94Updated 2 years ago
- An introduction to data science in Python, for people with no programming experience.☆467Updated 8 months ago
- Lecture materials for Cornell CS5785 Applied Machine Learning (Fall 2024)☆525Updated 2 months ago