awesome-scikit-learn

A curated list of awesome scikit-learn resources and libraries
https://github.com/fkromer/awesome-scikit-learn

Last synced: about 3 hours ago
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Algorithms
- scikit-cmeans - C-means fuzzy clustering algorithms.
- scikit-dda - Scikit-learn-compatible Deep Discriminant Analysis.
- scikit-garden - A garden of scikit-learn compatible trees.
- scikit-keras - Scikit-learn-compatible Keras models.
- scikit-MDR - A sklearn-compatible Python implementation of Multifactor Dimensionality Reduction (MDR) for feature construction.
- scikit-network - Network graph algorithms.
- scikit-sos - Stochastic Outlier Selection (SOS) for detecting outliers.
- scikit-splearn - Toolbox for spectral learning algorithms.
Books
- Advanced Machine Learning with Python (1st edition, 2016)
- Building Machine Learning Systems with Python - [Companion code](https://github.com/luispedro/BuildingMachineLearningSystemsWithPython).
- Introduction to Machine Learning with Python (1st edition, 2016)
- Large Scale Machine Learning with Python (1st edition, 2016)
- Learning scikit-learn: Machine Learning in Python (2013)
- Machine Learning with scikit-learn Quick Start Guide (1st edition, 2018)
- Mastering Machine Learning with Python in Six Steps (2nd edition, 2019)
- Mastering Machine Learning with scikit-learn (2nd edition, 2017)
- Mastering Predictive Analytics with scikit-learn and TensorFlow (1st edition, 2018)
- Python Machine Learning Cookbock (2nd edition, 2019)
- scikit-learn Cookbook (2nd edition, 2017) - [Companion code](https://github.com/PacktPublishing/scikit-learn-Cookbook-Second-Edition).
- Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data
- Advanced Machine Learning with Python (1st edition, 2016)
- Building Machine Learning Systems with Python - [Companion code](https://github.com/luispedro/BuildingMachineLearningSystemsWithPython).
- Large Scale Machine Learning with Python (1st edition, 2016)
- Learning scikit-learn: Machine Learning in Python (2013)
- Machine Learning with scikit-learn Quick Start Guide (1st edition, 2018)
- Mastering Machine Learning with scikit-learn (2nd edition, 2017)
- Mastering Predictive Analytics with scikit-learn and TensorFlow (1st edition, 2018)
- Python Machine Learning Cookbock (2nd edition, 2019)
- scikit-learn Cookbook (2nd edition, 2017) - [Companion code](https://github.com/PacktPublishing/scikit-learn-Cookbook-Second-Edition).
Documentation
- API Reference
- Quick Start Tutorial
Examples
- scikit-learn Example Gallery - Official scikit-learn docs examples.
Extensions
- scikit-datasets - Scikit-learn-compatible datasets.
- sklearn-onnx - Convert your scikit-learn model into ONNX.
- scikit-onnxruntime - Scikit-learn wrapper of onnxruntime.
- scikit-vis - Adds gorgeous, easy-to-use graphics to the massively popular scikit-learn.
- sklearn-xarray - Wrappers that allow the user to apply scikit-learn estimators to xarray types (tensors) without losing their labels.
- SciPy - List of scikits - Very incomplete list of extensions for SciPy helpful e.g. for domain specific work/integration with scikit-learn.
- SciPy - Topical software - List of software which can be helpful when working in the SciPy universe.
Frameworks
- Frameworks built on top of scikit-learn
  - ML-ENS - High performance ensemble learning: ML-ENS combines a Scikit-learn high-level API with a low-level computational graph framework to build memory efficient, maximally parallelized ensemble networks in as few lines of codes as possible.
  - modAL - A modular active learning framework.
  - nilearn - Machine learning for Neuro-Imaging.
  - tslearn - Machine learning tools for the analysis of time series.
  - SciKit-Learn Laboratory (SKLL)
- Frameworks scikit-learn is built on top of
  - Matplotlib - Comprehensive 2D Plotting.
  - numpy - Base N-dimensional array package.
  - pandas - Data structures & analysis.
MOOCs
- Frameworks scikit-learn is built on top of
  - Feature Engineering for Machine Learning (udemy.com)
  - Feature Selection for Machine Learning (udemy.com)
Papers
- Frameworks scikit-learn is built on top of
  - Scikit-learn: Machine Learning in Python (2011)
  - API design for machine learning software: experiences from the scikit-learn project
Presentations
Applications
- dash-svm - Interactive exploration of Support Vector Machine (SVM).

Programming Languages

Categories

Books 21 Presentations 17 Algorithms 8 Frameworks 8 Extensions 7 MOOCs 2 Documentation 2 Papers 2 Applications 1 Examples 1

Sub Categories

Frameworks scikit-learn is built on top of 7 Frameworks built on top of scikit-learn 5 2013 4 2018 3 2017 3 2015 3 2019 2 2016 1 2014 1

Keywords

svm 1 scikit-learn 1 plotly-dash 1 dash 1