Alternatives and similar repositories for mglearn:

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

• PacktPublishing / Bayesian-Analysis-with-Python
  Bayesian Analysis with Python by Packt
  ☆217Updated 2 years ago
• amueller / scipy-2018-sklearn
  Scipy 2018 scikit-learn tutorial by Guillaume Lemaitre and Andreas Mueller
  ☆248Updated 6 years ago
• elegant-scipy / notebooks
  The compiled, clean (not run) Jupyter notebooks for Elegant SciPy
  ☆111Updated 5 years ago
• justmarkham / pycon-2018-tutorial
  Using pandas for Better (and Worse) Data Science
  ☆322Updated 5 years ago
• WillKoehrsen / probabilistic-programming
  Experimenting with and teaching probabilistic programming
  ☆104Updated 2 years ago
• s-heisler / pycon2017-optimizing-pandas
  Materials for PyCon 2017 presentation on optimizing Pandas code
  ☆213Updated 5 years ago
• PacktPublishing / PythonDataAnalysisCookbook
  Python Data Analysis Cookbook, published by Packt
  ☆130Updated 4 years ago
• amueller / ml-workshop-1-of-4
  Introduction to Machine learning with Python, 4h interactive workshop
  ☆310Updated 5 years ago
• fonnesbeck / scipy2014_tutorial
  Tutorial: Bayesian Statistical Analysis in Python
  ☆318Updated 5 years ago
• amueller / scipy-2016-sklearn
  Scikit-learn tutorial at SciPy2016
  ☆516Updated 6 years ago
• tkrabel / edaviz
  edaviz - Python library for Exploratory Data Analysis and Visualization in Jupyter Notebook or Jupyter Lab
  ☆224Updated 5 years ago
• AllenDowney / CompStats
  Code for a workshop on statistical interference using computational methods in Python.
  ☆224Updated 4 years ago
• unpingco / Python-for-Probability-Statistics-and-Machine-Learning
  Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"
  ☆772Updated 2 years ago
• parrt / random-forest-importances
  Code to compute permutation and drop-column importances in Python scikit-learn models
  ☆611Updated last month
• fonnesbeck / intro_stat_modeling_2017
  Introduction to Statistical Modeling with Python (PyCon 2017)
  ☆166Updated 4 years ago
• jakevdp / sklearn_scipy2013
  Scikit-learn tutorials for the Scipy 2013 conference
  ☆325Updated 7 years ago
• AllenDowney / BayesMadeSimple
  Code for a tutorial on Bayesian Statistics by Allen Downey.
  ☆351Updated 4 years ago
• bokeh / bokeh-notebooks
  Interactive Web Plotting with Bokeh in IPython notebook
  ☆734Updated last year
• LeiG / Applied-Predictive-Modeling-with-Python
  A collection of notebook to learn the Applied Predictive Modeling using Python.
  ☆275Updated 8 years ago
• PacktPublishing / Mastering-Machine-Learning-with-scikit-learn-Second-Edition
  Mastering Machine Learning with scikit learn Second Edition, published by Packt
  ☆81Updated 4 years ago
• cliburn / Computational-statistics-with-Python
  Resources for STA 633 class
  ☆167Updated 7 years ago
• ikding / pycon_time_series
  PyCon 2017 tutorial on time series analysis
  ☆72Updated 7 years ago
• amueller / scipy-2017-sklearn
  Scipy 2017 scikit-learn tutorial by Alex Gramfort and Andreas Mueller
  ☆285Updated 7 years ago
• rasbt / data-science-tutorial
  Code material for a data science tutorial
  ☆198Updated 7 years ago
• WillKoehrsen / Bokeh-Python-Visualization
  A Bokeh project developed for learning and teaching Bokeh interactive plotting!
  ☆363Updated 3 years ago
• PacktPublishing / Practical-Time-Series-Analysis
  Practical Time-Series Analysis, published by Packt
  ☆407Updated 2 years ago
• JWarmenhoven / DBDA-python
  Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code
  ☆679Updated 3 years ago
• ipython-books / minibook-2nd-code
  Code of the IPython Minibook, 2nd edition (2015)
  ☆346Updated 4 years ago
• brinkar / real-world-machine-learning
  Code accompanying the Real-World Machine Learning book
  ☆324Updated 8 years ago
• amueller / ml-training-advanced
  Materials for the "Advanced Scikit-learn" class in the afternoon
  ☆165Updated 6 years ago