Alternatives and similar repositories for the-elements-of-statistical-learning

Users that are interested in the-elements-of-statistical-learning are comparing it to the libraries listed below

• empathy87 / The-Elements-of-Statistical-Learning-Python-Notebooks
  A series of Python Jupyter notebooks that help you better understand "The Elements of Statistical Learning" book
  ☆908Updated 4 years ago
• emredjan / ISL-python
  Porting the R code in ISL to python. Labs and exercises
  ☆203Updated 3 years ago
• jcrouser / islr-python
  ☆110Updated 4 years ago
• shilpa9a / Introduction_to_statistical_learning_summary_python
  Summary of each chapter of the book- Introduction of Statistical Learning (ISL), along with Python code & data.
  ☆188Updated last year
• amueller / COMS4995-s20
  COMS W4995 Applied Machine Learning - Spring 20
  ☆245Updated 3 years ago
• dgkim5360 / the-elements-of-statistical-learning-notebooks
  Jupyter notebooks for summarizing and reproducing the textbook "The Elements of Statistical Learning" 2/E by Hastie, Tibshirani, and Frie…
  ☆294Updated 7 years ago
• qx0731 / Sharing_ISL_python
  An Introduction to Statistical Learning with Applications in PYTHON
  ☆555Updated 4 years ago
• unpingco / Python-for-Probability-Statistics-and-Machine-Learning-2E
  Second edition of Springer Book Python for Probability, Statistics, and Machine Learning
  ☆372Updated 4 years ago
• tdpetrou / Machine-Learning-Books-With-Python
  Chapter by Chapter notes, exercises and code for a variety of machine learning books using Python
  ☆941Updated 3 years ago
• tirthajyoti / Stats-Maths-with-Python
  General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python
  ☆980Updated 3 years ago
• a-martyn / ISL-python
  Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.
  ☆345Updated last year
• LeiG / Applied-Predictive-Modeling-with-Python
  A collection of notebook to learn the Applied Predictive Modeling using Python.
  ☆283Updated 9 years ago
• tdg5 / stats-learning-notes
  Notes from Introduction to Statistical Learning
  ☆120Updated 7 years ago
• JWarmenhoven / DBDA-python
  Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code
  ☆691Updated 4 years ago
• vbartle / MML-Companion
  This is a companion to the ‘Mathematical Foundations’ section of the book, Mathematics for Machine Learning by Marc Deisenroth, Aldo Fais…
  ☆297Updated 5 years ago
• briandalessandro / DataScienceCourse
  This holds iPython notebooks and lecture slides for the Intro to Data Science Master's course I teach at NYU.
  ☆757Updated 5 years ago
• ericmjl / bayesian-stats-modelling-tutorial
  How to do Bayesian statistical modelling using numpy and PyMC3
  ☆672Updated 3 years ago
• davidrosenberg / mlcourse
  Machine learning course materials.
  ☆578Updated 2 years ago
• jessicayung / machine-learning-flashcards
  Machine learning flashcards
  ☆223Updated 4 years ago
• parrt / msds621
  Course notes for MSDS621 at Univ of San Francisco, introduction to machine learning
  ☆347Updated 4 years ago
• AllenDowney / BayesMadeSimple
  Code for a tutorial on Bayesian Statistics by Allen Downey.
  ☆357Updated 5 years ago
• unpingco / Python-for-Probability-Statistics-and-Machine-Learning
  Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"
  ☆793Updated 3 years ago
• Harvard-IACS / 2020-CS109A
  ☆120Updated 3 years ago
• fonnesbeck / Bayes_Computing_Course
  ☆234Updated 4 years ago
• TraceMyers / mitx-stats-notes
  Notes for 18.6501x, Fundamentals of Statistics on edX
  ☆96Updated 3 years ago
• WillKoehrsen / probabilistic-programming
  Experimenting with and teaching probabilistic programming
  ☆107Updated 3 years ago
• leomiolane / linalg-for-ds
  Linear Algebra and Optimization for Data Science
  ☆24Updated 5 years ago
• rasbt / stat479-deep-learning-ss19
  Course material for STAT 479: Deep Learning (SS 2019) at University Wisconsin-Madison
  ☆546Updated 6 years ago
• rasbt / stat479-machine-learning-fs19
  Course material for STAT 479: Machine Learning (FS 2019) taught by Sebastian Raschka at University Wisconsin-Madison
  ☆780Updated 5 years ago
• davidyakobovitch / data_science_resources
  📊 Data Science Resources, Data Science Standards & Machine Learning Pipelines
  ☆161Updated 3 years ago