niuers / Linear-Algebra-and-Learning-from-Data
Solutions to the problems in the book: Linear Algebra and Learning from Data by Gilbert Strang, MIT
☆263Updated 2 years ago
Alternatives and similar repositories for Linear-Algebra-and-Learning-from-Data:
Users that are interested in Linear-Algebra-and-Learning-from-Data are comparing it to the libraries listed below
- Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.☆325Updated 8 months ago
- Solutions to the exercises and problems in the book: Learn From Data_A Short Course by Yaser Abu-Mostafa, Malik Magdon-Ismail and Hsuan-T…☆234Updated 2 years ago
- My solutions to DLFC - Deep Learning: Foundations and Concepts☆69Updated 4 months ago
- ☆222Updated 2 years ago
- All notes and materials for the CS229: Machine Learning course by Stanford University☆214Updated 3 years ago
- Self-study on Larry Wasserman's "All of Statistics"☆1,051Updated 2 years ago
- undergraduate numerical analysis course in MIT☆36Updated 4 years ago
- Stanford convex optimization course☆84Updated 4 years ago
- NYU Course Notes & Resources☆187Updated 10 months ago
- A series of Python Jupyter notebooks that help you better understand "The Elements of Statistical Learning" book☆873Updated 3 years ago
- MIT IAP short course: Matrix Calculus for Machine Learning and Beyond☆391Updated last month
- Solutions to Linear Algebra Done Right, by Sheldon Axler.☆292Updated 7 months ago
- 🌲 Stanford CS 228 - Probabilistic Graphical Models☆126Updated 6 months ago
- Solutions to exercises from Introduction to Statistical Learning (ISLR 1st Edition)☆176Updated 2 years ago
- Additional exercises and data for EE364a. No solutions; for public consumption.☆667Updated last month
- Shortest solutions for CS231n 2021-2024☆304Updated 10 months ago
- Solutions to All of Statistics, a textbook authored by Larry Wasserman. I wrote the solutions as a self-studying method, thus I cannot gu…☆21Updated 3 years ago
- This is a companion to the ‘Mathematical Foundations’ section of the book, Mathematics for Machine Learning by Marc Deisenroth, Aldo Fais…☆268Updated 4 years ago
- Material for the "Probabilistic Machine Learning" Course at the University of Tübingen, Summer Term 2023☆147Updated last year
- 🌀 Stanford CS 228 - Probabilistic Graphical Models☆81Updated 6 years ago
- These are companion notebooks written in Julia and Python for: "Introduction to Applied Linear Algebra" by Boyd and Vandenberghe.☆332Updated 4 years ago
- ☆270Updated 2 years ago
- Solutions to 'An Introduction to Statistical Learning with Applications in R'... in Python!☆31Updated 7 months ago
- ☆39Updated 4 months ago
- Material for The Mathematical Engineering of Deep Learning. See https://deeplearningmath.org☆443Updated 7 months ago
- Collection of my assignments and work in the class MATH51 at Stanford☆92Updated 10 years ago
- My notes from class☆64Updated 6 years ago
- ☆77Updated 4 years ago
- Own solutions for exercises and MATLAB example codes for "Numerical Linear Algebra" by Lloyd N. Trefethen and David Bau III, 1997☆71Updated last year
- Solutions for David Barber's "Bayesian Reasoning and Machine Learning" Book☆19Updated 3 years ago