Process of automating the process of applying machine learning to real-world problems. AutoML covers the complete pipeline from the raw dataset to the deployable machine learning model. AutoML was proposed as an artificial intelligence-based solution to the ever-growing challenge of applying machine learning. The high degree of automation in AutoML allows non-experts to make use of machine learning models and techniques without requiring to become an expert in this field first.

Libraries

General
Pycaret
An open source, low-code machine learning library in Python.
automl pycaret preprocessing library
Auto-sklearn
Automated Machine Learning with scikit-learn.
automl scikit-learn library research
AutoGOAL
A Python framework for Automated Machine Learning (AutoML), hyperparameter tunning and program synthesis in general.
automl python machine-learning code
Lazy Predict
Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning.
automl lazypredict regression classification
Mljar-supervised
✨ Automated Machine Learning Python package designed to save time for a data scientist 😎
automl supervised-learning linear-regression multi-class-classification
TPOT: Tree-based Pipeline Optimization Tool
TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
automl tpot genetic-programming hyperparameter-optimization
Star Clustering
A clustering algorithm that automatically determines the number of clusters and works without hyperparameter fine-tuning.
clustering automl library code
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