Alternatives and similar repositories for 186501xStatistics

Users that are interested in 186501xStatistics are comparing it to the libraries listed below

• mynameisjanus / 6431xProbability
  CheatSheet for 6.431x
  ☆16Updated 5 years ago
• mynameisjanus / 14310xDataAnalysis
  CheatSheet for 14.310x
  ☆11Updated 5 years ago
• blechturm / cheatsheet-18.6501x
  Community based cheatsheet for the MITx course 18.6501x Fundamentals of Statistics
  ☆44Updated 5 years ago
• TraceMyers / mitx-stats-notes
  Notes for 18.6501x, Fundamentals of Statistics on edX
  ☆96Updated 3 years ago
• blechturm / MITx_capstone_2
  This is the second cheatsheet for the MITx capstone exams for Statistics and Datascience
  ☆24Updated 4 years ago
• sylvaticus / MITx_6.86x
  Notes of MITx 6.86x - Machine Learning with Python: from Linear Models to Deep Learning
  ☆332Updated last year
• blechturm / MITx_capstone_1
  This is the first cheat-sheet for the MITx Statistics and Datascience capstone exam
  ☆40Updated 5 years ago
• Varal7 / ml-tutorial
  Introduction to ML packages for the 6.86x course
  ☆403Updated 5 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.
  ☆185Updated last year
• amueller / ml-workshop-1-of-4
  Introduction to Machine learning with Python, 4h interactive workshop
  ☆312Updated 5 years ago
• mynameisjanus / 686xMachineLearning
  CheatSheet for 6.86x
  ☆24Updated 5 years ago
• amueller / COMS4995-s20
  COMS W4995 Applied Machine Learning - Spring 20
  ☆245Updated 3 years ago
• vbartle / VMLS-Companions
  These are companion notebooks written in Julia and Python for: "Introduction to Applied Linear Algebra" by Boyd and Vandenberghe.
  ☆346Updated 5 years ago
• emredjan / ISL-python
  Porting the R code in ISL to python. Labs and exercises
  ☆203Updated 3 years ago
• 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…
  ☆422Updated 2 months ago
• Harvard-IACS / 2019-CS109B
  ☆62Updated 6 years ago
• dnackat / mitx-6.86x-machine-learning
  Python code written for MIT's Machine Learning course offered on edX
  ☆125Updated 6 years ago
• skasch / fundamentals-of-statistics
  Notes on Fundamentals of Statistics course
  ☆15Updated 6 years ago
• Montanaz0r / Bayesian-Statistics-The-Fun-Way
  Solutions and workflow for the Bayesian Statistics The Fun Way book in Python
  ☆75Updated last year
• Harvard-IACS / 2018-CS109A
  Repository for CS109A Fall 2018
  ☆149Updated 5 years ago
• Yolanda-HT / MIT_6.419x
  Data Analysis: Statistical Modeling and Computation in Applications
  ☆60Updated 4 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
  ☆902Updated 4 years ago
• tdg5 / stats-learning-notes
  Notes from Introduction to Statistical Learning
  ☆118Updated 7 years ago
• Harvard-IACS / 2020-CS109A
  ☆118Updated 3 years ago
• gbosquechacon / statrethink_course_in_pymc3
  Statistical Rethinking course in pymc3
  ☆144Updated 5 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…
  ☆296Updated 5 years ago
• parrt / msds621
  Course notes for MSDS621 at Univ of San Francisco, introduction to machine learning
  ☆346Updated 4 years ago
• jbernhard-nw / rec-workshop
  Getting started
  ☆19Updated 5 years ago
• mattharrison / ml_pocket_reference
  Resources for Machine Learning Pocket Reference
  ☆268Updated 4 years ago