Alternatives and similar repositories for featuretools

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

• DistrictDataLabs / yellowbrick
  Visual analysis and diagnostic tools to facilitate machine learning model selection.
  ☆4,395Updated 11 months ago
• TeamHG-Memex / eli5
  A library for debugging/inspecting machine learning classifiers and explaining their predictions
  ☆2,771Updated 2 weeks ago
• EpistasisLab / tpot
  A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
  ☆10,047Updated 4 months ago
• automl / auto-sklearn
  Automated Machine Learning with scikit-learn
  ☆8,048Updated 3 weeks ago
• scikit-learn-contrib / imbalanced-learn
  A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
  ☆7,078Updated last week
• scikit-learn-contrib / category_encoders
  A library of sklearn compatible categorical variable encoders
  ☆2,479Updated last month
• rasbt / mlxtend
  A library of extension and helper modules for Python's data analysis and machine learning libraries.
  ☆5,110Updated 2 weeks ago
• ClimbsRocks / auto_ml
  [UNMAINTAINED] Automated machine learning for analytics & production
  ☆1,657Updated 5 years ago
• hyperopt / hyperopt
  Distributed Asynchronous Hyperparameter Optimization in Python
  ☆7,616Updated 3 weeks ago
• parrt / dtreeviz
  A python library for decision tree visualization and model interpretation.
  ☆3,124Updated last month
• WillKoehrsen / feature-selector
  Feature selector is a tool for dimensionality reduction of machine learning datasets
  ☆2,237Updated last year
• AxeldeRomblay / MLBox
  MLBox is a powerful Automated Machine Learning python library.
  ☆1,527Updated 2 years ago
• scikit-optimize / scikit-optimize
  Sequential model-based optimization with a `scipy.optimize` interface
  ☆2,811Updated last year
• blue-yonder / tsfresh
  Automatic extraction of relevant features from time series:
  ☆9,109Updated 2 months ago
• hyperopt / hyperopt-sklearn
  Hyper-parameter optimization for sklearn
  ☆1,646Updated 9 months ago
• scikit-learn-contrib / sklearn-pandas
  Pandas integration with sklearn
  ☆2,848Updated 2 years ago
• interpretml / interpret
  Fit interpretable models. Explain blackbox machine learning.
  ☆6,790Updated this week
• scikit-learn-contrib / boruta_py
  Python implementations of the Boruta all-relevant feature selection method.
  ☆1,618Updated 2 months ago
• reiinakano / scikit-plot
  An intuitive library to add plotting functionality to scikit-learn objects.
  ☆2,434Updated last year
• marcotcr / lime
  Lime: Explaining the predictions of any machine learning classifier
  ☆12,095Updated last year
• feature-engine / feature_engine
  Feature engineering and selection open-source Python library compatible with sklearn.
  ☆2,194Updated this week
• mljar / mljar-supervised
  Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
  ☆3,240Updated 7 months ago
• keras-team / autokeras
  AutoML library for deep learning
  ☆9,307Updated 2 months ago
• snorkel-team / snorkel
  A system for quickly generating training data with weak supervision
  ☆5,938Updated last year
• vaexio / vaex
  Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per s…
  ☆8,468Updated this week
• ResidentMario / missingno
  Missing data visualization module for Python.
  ☆4,184Updated last year
• jmcarpenter2 / swifter
  A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner
  ☆2,642Updated last year
• stanfordmlgroup / ngboost
  Natural Gradient Boosting for Probabilistic Prediction
  ☆1,825Updated 2 months ago
• catboost / catboost
  A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other ma…
  ☆8,789Updated this week
• yzhao062 / pyod
  A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
  ☆9,696Updated last month