Scikit-learn is a machine-learning library in Python. It creates accessible and easy to use tools for data mining and data analysis. Built on NumPy, SciPy and matplotlib, the project is open source and available for commercial use with a BSD license.

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    We would like to hear the opinions of machine learning practitioners on machine learning experiment management tools. Experiment management tools support practitioners performing machine learning (ML) or deep learning (DL) experiments to manage all involved artifacts and metadata (datasets, features, scripts, hyperparameters, evaluation metrics, models, …). Such tools are used to reproduce or trace experiments, analyze experiment results, and collaborate with other practitioners. Popular tools are, for instance, , DVC, or MLFlow. These tools allow users to track or log artifacts when performing experiment runs. Completing the survey takes approximately 10 minutes for each ML practitioner. Due to project constraints, we can only pay a maximum of 15 USD.

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