dgkim5360 / the-elements-of-statistical-learning-notebooksLinks
Jupyter notebooks for summarizing and reproducing the textbook "The Elements of Statistical Learning" 2/E by Hastie, Tibshirani, and Friedman
☆287Updated 7 years ago
Alternatives and similar repositories for the-elements-of-statistical-learning-notebooks
Users that are interested in the-elements-of-statistical-learning-notebooks are comparing it to the libraries listed below
Sorting:
- My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Frie…☆412Updated 3 years ago
- A series of Python Jupyter notebooks that help you better understand "The Elements of Statistical Learning" book☆887Updated 3 years ago
- COMS W4995 Applied Machine Learning - Spring 19☆301Updated 5 years ago
- Exercises from 'Introduction to Statistical Learning with Applications in R' written in Python.☆105Updated 7 years ago
- ☆107Updated 3 years ago
- Machine learning course materials.☆572Updated last year
- Materials for "Bayesian Methods for Machine Learning" Coursera MOOC☆134Updated 4 years ago
- Code and data for the second edition of the textbook `Machine Learning: An Algorithm Perspective" by Stephen Marsland.☆150Updated 4 years ago
- Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code☆682Updated 3 years ago
- Course page for DS-GA 3001.001 Modeling Time Series Data☆43Updated 7 years ago
- Course notes for Computational Statistics and Statistical Compuing☆63Updated 6 years ago
- Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"☆775Updated 2 years ago
- Jupyter notebooks with the Python equivalent to the R code sections in Blitzstein and Hwang's Introduction To Probability, Second Edition☆73Updated 6 years ago
- Jupyter Notebooks for Computational Linear Algebra course, taught summer 2018 in USF MSDS program☆274Updated 6 years ago
- ☆231Updated 3 years ago
- A collection of notebook to learn the Applied Predictive Modeling using Python.☆275Updated 8 years ago
- Bayesian Analysis with Python by Packt☆217Updated 2 years ago
- Collaborative lecture notes for Spring '19 NYU DL class☆119Updated 5 years ago
- My solution to the book A Collection of Data Science Take-Home Challenges☆25Updated 6 years ago
- COMS W4995 Applied Machine Learning - Spring 20☆246Updated 3 years ago
- Python notebooks for exercises covered in Stanford statlearning class (where exercises were in R).☆379Updated 9 years ago
- Python implementations (on jupyter notebook) of algorithms described in the book "PRML"☆253Updated 3 years ago
- COMS W4995 Applied Machine Learning - Spring 18☆158Updated 6 years ago
- Resources for STA 633 class☆169Updated 8 years ago
- Statistical Learning Theory (CS229T) Lecture Notes☆717Updated 5 years ago
- Course material for STAT 479: Deep Learning (SS 2019) at University Wisconsin-Madison☆534Updated 6 years ago
- Tutorials on visualizing data using python packages like bokeh, plotly, seaborn and igraph☆267Updated 4 years ago
- Porting the R code in ISL to python. Labs and exercises☆196Updated 2 years ago
- Solutions to Wasserman's 'All of Statistics'.☆104Updated 6 years ago
- Compilation of resources found around the web connected with Machine Learning, Deep Learning & Data Science in general.☆92Updated 7 years ago