dotData Further Accelerates Data Science Automation with the Launch of dotDataPy

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According to a recent press release, “dotData, the first and only company focused on delivering end-to-end data science automation and operationalization for the enterprise, today announced the launch of dotDataPy, a lightweight and scalable Python library that enables advanced users to access dotData’s data science automation functionality, including AI-powered feature engineering and automated machine learning. With just a few lines of code, data scientists can now create, execute and validate end-to-end data science pipelines.”

The release continues, “dotDataPy can be easily integrated with Jupyter notebooks and other Python development environments, enabling users to fully leverage the advanced Python ecosystem, including rich visualization (e.g. Matplotlib and Plotly), state-of-the-art machine learning/deep learning tools (e.g. scikit-learn, Spark MLlib, PyTorch, and TensorFlow), and flexible DataFrames (e.g. pandas and PySpark). dotDataPy enables greater flexibility through its Python interface, and empowers data scientists to achieve higher productivity and drive greater business impact than ever before.”

It adds, “dotData’s AI-powered Data Science Automation Platform completely automates the entire data science process, from data collection through production-ready models, including feature engineering. As a result, the entire data science process is accelerated from months to days, enabling companies to rapidly scale their AI/ML initiatives to drive transformative business changes.”

Read more at dotData.com.

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