Alternatives and similar repositories for np-learn:

Users that are interested in np-learn are comparing it to the libraries listed below

• ronojoy / pylearn
  Bayesian machine learning in Python
  ☆76Updated 9 years ago
• GaelVaroquaux / interpreting_ml_tuto
  Tutorial on interpreting and understanding machine learning models
  ☆68Updated 6 years ago
• pierreablin / autoptim
  Automatic differentiation + optimization
  ☆103Updated 6 years ago
• yandexdataschool / MLatGradDays
  Course of Machine Learning in Science and Industry at Heidelberg university
  ☆47Updated 7 years ago
• chendaniely / scipy_2016_notes
  ☆52Updated 8 years ago
• EFavDB / linselect
  ☆89Updated 6 years ago
• mitdbg / fastdeepnets
  ☆113Updated 2 years ago
• stitchfix / diamond
  Python solver for mixed-effects models
  ☆98Updated 7 years ago
• alexandraj777 / machine-learning-samples
  Sample applications built using AWS' Amazon Machine Learning.
  ☆51Updated 7 years ago
• amueller / advanced_git_nyu_2016
  Advanced git and github course material
  ☆39Updated 7 years ago
• mrocklin / dask-workshop
  ☆28Updated 7 years ago
• tmadl / sklearn-interpretable-tree
  Simplified tree-based classifier and regressor for interpretable machine learning (scikit-learn compatible)
  ☆47Updated 4 years ago
• yell / mnist-challenge
  My solution to TUM's Machine Learning MNIST challenge 2016-2017 [winner]
  ☆70Updated 5 years ago
• junpenglao / Bayesian-Cognitive-Modeling-in-Pymc3
  PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course
  ☆96Updated 7 years ago
• JackCaster / Intro_to_PyMC3
  Short introduction to Bayesian statistical modelling with PyMC3
  ☆18Updated 5 years ago
• ContextLab / hypertools-paper-notebooks
  Supporting notebooks and data from hypertools paper
  ☆147Updated 6 years ago
• fonnesbeck / scipy2015_tutorial
  Computational Statistics II Tutorial at SciPy 2015
  ☆48Updated 9 years ago
• tdhopper / pydata-nyc-2015
  Understanding Probabilistic Topic Models with Simulation in Python
  ☆64Updated 7 years ago
• pydataberlin / conf2017slides
  ☆57Updated 7 years ago
• arogozhnikov / infiniteboost
  InfiniteBoost: building infinite ensembles with gradient descent
  ☆184Updated 6 years ago
• jseabold / odsc-west-python-2017
  Introduction to Python for Data Science
  ☆39Updated 7 years ago
• rasbt / pydata-annarbor2017-dl-tutorial
  Code snippets for "Introduction to Deep Learning with TensorFlow" at PyData Ann Arbor Aug 2017
  ☆79Updated 7 years ago
• AllenDowney / BayesSeminar
  Bayesian statistics seminars
  ☆30Updated 7 years ago
• ioam / jupytercon2017-holoviews-tutorial
  HoloViews+Bokeh tutorial for JupyterCon 2017
  ☆51Updated 2 years ago
• amueller / advanced_training
  Advanced Scikit-learn training session
  ☆118Updated 8 years ago
• jfsantos / keras-tutorial
  Tutorial teaching the basics of Keras and some deep learning concepts
  ☆104Updated 8 years ago
• jupyterlab / scipy2018-jupyterlab-tutorial
  Tutorial material and instruction for scipy 2018 jupyterlab tutorial
  ☆73Updated 6 years ago
• odewahn / computational-publishing
  ☆66Updated 7 years ago
• GaelVaroquaux / sklearn_europython_2014
  Scikit-learn Tutorial at EuroPython 2014
  ☆43Updated 6 years ago
• glouppe / talk-pydata2015
  Talk on "Tree models with Scikit-Learn: Great learners with little assumptions" presented at PyPata Paris 2015
  ☆50Updated 9 years ago