Alternatives and similar repositories for 2021-CS109B

Users that are interested in 2021-CS109B are comparing it to the libraries listed below

• Harvard-IACS / 2020-CS109A
  ☆114Updated 3 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…
  ☆284Updated 4 years ago
• qx0731 / Sharing_ISL_python
  An Introduction to Statistical Learning with Applications in PYTHON
  ☆544Updated 3 years ago
• Harvard-IACS / 2021-CS109A
  ☆139Updated 3 years ago
• PacktPublishing / Interpretable-Machine-Learning-with-Python
  Interpretable Machine Learning with Python, published by Packt
  ☆470Updated 2 years ago
• 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
  ☆899Updated 4 years ago
• PacktPublishing / Hands-On-Gradient-Boosting-with-XGBoost-and-Scikit-learn
  Hands-On Gradient Boosting with XGBoost and Scikit-learn Published by Packt
  ☆211Updated 3 months ago
• TraceMyers / mitx-stats-notes
  Notes for 18.6501x, Fundamentals of Statistics on edX
  ☆96Updated 3 years ago
• rasbt / stat451-machine-learning-fs20
  STAT 451: Intro to Machine Learning @ UW-Madison (Fall 2020)
  ☆431Updated 10 months ago
• rasbt / stat451-machine-learning-fs21
  ☆151Updated 3 years ago
• a-martyn / ISL-python
  Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.
  ☆336Updated last year
• parrt / msds621
  Course notes for MSDS621 at Univ of San Francisco, introduction to machine learning
  ☆348Updated 3 years ago
• amueller / COMS4995-s20
  COMS W4995 Applied Machine Learning - Spring 20
  ☆247Updated 3 years ago
• Peacock-Biscuit / data-science-fundamentals
  The repository is to document skills that a data scientist needs to acquire
  ☆19Updated 3 weeks ago
• Harvard-IACS / 2018-CS109A
  Repository for CS109A Fall 2018
  ☆149Updated 4 years ago
• ml874 / Cracking-the-Data-Science-Interview
  Cracking the Data Science Interview
  ☆357Updated 5 years ago
• matheusfacure / causal-inference-in-python-code
  Code for the Book Causal Inference in Python
  ☆329Updated last year
• shilpa9a / Introduction_to_statistical_learning_summary_python
  Summary of each chapter of the book- Introduction of Statistical Learning (ISL), along with Python code & data.
  ☆185Updated last year
• maitbayev / the-elements-of-statistical-learning
  My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Frie…
  ☆416Updated 3 years ago
• emredjan / ISL-python
  Porting the R code in ISL to python. Labs and exercises
  ☆200Updated 3 years ago
• PacktPublishing / Python-Feature-Engineering-Cookbook
  Python Feature Engineering Cookbook, published by Packt
  ☆481Updated 2 years ago
• zgana / fpp3-python-readalong
  Python-centered read-along of Forecasting: Principles and Practice
  ☆507Updated 11 months ago
• INRIA / scikit-learn-mooc
  Machine learning in Python with scikit-learn MOOC
  ☆1,261Updated 2 weeks ago
• davidrosenberg / mlcourse
  Machine learning course materials.
  ☆573Updated last year
• jcrouser / islr-python
  ☆110Updated 4 years ago
• Brandon-HY-Lin / coursera_How-to-Win-a-Data-Science-Competition-Learn-from-Top-Kagglers
  Labs and Project from the course "How to Win a Data Science Competition: Learn from Top Kagglers"
  ☆147Updated 5 years ago
• rasbt / stat453-deep-learning-ss21
  STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2021)
  ☆510Updated 3 years ago
• numeristical / resources
  A collection of resources for learning and research.
  ☆97Updated 3 months ago
• tdpetrou / Machine-Learning-Books-With-Python
  Chapter by Chapter notes, exercises and code for a variety of machine learning books using Python
  ☆938Updated 2 years ago
• sylvaticus / MITx_6.86x
  Notes of MITx 6.86x - Machine Learning with Python: from Linear Models to Deep Learning
  ☆324Updated last year