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Build and deploy predictive models effortlessly with MLbox. Simplify the process with automated data preprocessing, feature engineering, and model selection. Ideal for data scientists and analysts.

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What is MLbox?

MLbox is an automated machine learning tool that simplifies the process of creating and implementing predictive models. It offers a comprehensive solution for transforming data, engineering features, selecting models, optimizing hyperparameters, and deploying models. With MLbox, users can effortlessly build and deploy accurate predictive models without extensive technical knowledge. The tool is designed to be intuitive and user-friendly, allowing even those with limited expertise to quickly get started. MLbox also provides advanced features such as automated data preprocessing, feature engineering, model selection, tuning, deployment, and monitoring. Additionally, MLbox generates detailed reports and visualizations to help users understand the performance of their models. This tool is particularly beneficial for data scientists, data analysts, and anyone who needs to rapidly and reliably construct and deploy predictive models.


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MLbox Use Cases

MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cleaning/formatting. Highly robust feature selection and leak detection. Accurate hyper-parameter optimization in high-dimensional space. State-of-the art predictive models for classification and regression (Deep Learning, Stacking, LightGBM,…). Prediction with models interpretation.

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