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ABSTRACT
Auto-ML sets out as connection joining the different levels of competence when
building Machine learning pipelines or systems and achieve the data science
processes more quickly. We present the common Automl tool which works on
cleaned datasets using normal Ready-made algorithms provided by sklearn to run
against regression and classification datasets and we also use the open source
Automl libraries like auto-sklearn,hyperpot,Tpot etc and found that TPOT is best
suitable for the regression datasets and auto-sklearn is best suitable for the
classification datasets .The auto sklearn library is basically used for running the auto-
ml . By using the scikit-learn machine learning library we can train the high level of
machine learning algorithms and can find best accuracy easily for the given dataset.
