minireference / noBSLAnotebooksLinks
Jupyter notebooks with exercises for the No bullshit guide to linear algebra.
☆234Updated last year
Alternatives and similar repositories for noBSLAnotebooks
Users that are interested in noBSLAnotebooks are comparing it to the libraries listed below
Sorting:
- Essential mathematics for applied machine learning and data science☆76Updated 3 years ago
- Introductory Statistical Inference☆146Updated last year
- Figure notebooks for "The Data Science Design Manual" (http://www.data-manual.com/)☆61Updated 8 years ago
- ML algorithms in depth☆253Updated 11 months ago
- Applied Probability Theory for Everyone☆116Updated 11 months ago
- This is a companion to the ‘Mathematical Foundations’ section of the book, Mathematics for Machine Learning by Marc Deisenroth, Aldo Fais…☆284Updated 4 years ago
- Jupyter notebooks with the Python equivalent to the R code sections in Blitzstein and Hwang's Introduction To Probability, Second Edition☆74Updated 6 years ago
- Specification files for the Foundations of Applied Mathematics lab curriculum. https://foundations-of-applied-mathematics.github.io/☆54Updated last year
- Machine Learning Algorithms Second Edition, published by Packt☆64Updated last year
- Supplementary material for my book, Probably Overthinking It.☆155Updated 2 weeks ago
- Jupyter Notebooks for Computational Linear Algebra course, taught summer 2018 in USF MSDS program☆275Updated 7 years ago
- Python code (in the form of Jupyter ipython notebooks) to support the book "Math and Architectures of Deep Learning" (Krishnendu Chaudhur…☆209Updated last year
- Second edition of Springer Book Python for Probability, Statistics, and Machine Learning☆363Updated 3 years ago
- Harvard CS109b Public Repository☆234Updated 4 years ago
- Python and MATLAB code for linear algebra textbook.☆186Updated 10 months ago
- Probability and Statistics Using Python Data Science Masters Course at UCSD (DSE 210)☆180Updated 8 years ago
- Mastering Machine Learning Algorithms Second Edition, published by Packt☆62Updated 4 years ago
- An introduction to data science in Python, for people with no programming experience.☆441Updated 2 months ago
- Code for Allen Downey's book Think Complexity, published by O'Reilly Media.☆113Updated 10 months ago
- Course notes for MSDS501, computational boot camp, at the University of San Francisco☆125Updated 4 years ago
- Notes taken from Google Machine Learning Course provided to public for practice & correction.☆203Updated 2 years ago
- Solutions to the exercises in Grinstead and Snell's Introduction to Probability☆88Updated 2 years ago
- CS50 Brown University☆61Updated 7 years ago
- An introduction to Bayesian statistics using Python and (coming soon) R.☆134Updated last year
- Notebooks for tutorial on Numpy.☆61Updated 5 years ago
- Deep Learning Study Group☆325Updated 4 years ago
- Code files added☆99Updated 2 years ago
- .pdf Format Books for Machine and Deep Learning☆247Updated 6 years ago
- All of the figures and notebooks for my deep learning book, for free!☆506Updated 2 months ago
- IPython notebooks on Gilbert Strang's MIT course on linear algebra (18.06)☆561Updated last year