AI automation solution for every data scientist’s laptop

AI automation solution for every data scientist’s laptop

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Machine learning company dotData has announced the launch of a new containerized AI automation solution to enable data scientists to execute quick proofs of concepts (POCs) and deploy AI automation on their desktop.
By Rich Pell


Offered as an affordable and powerful AI automation tool that boosts the productivity of Python data scientists, dotData Py Lite provides the company’s automated feature engineering and automated machine learning (ML) in a portable environment. It allows data scientists to explore 100x more features, augment their hypotheses, and improve their ML models quickly without having to rely on large and expensive enterprise-AI environments, says the company.

“Great machine learning algorithms do not guarantee great AI models – the secret is feature engineering,” says Ryohei Fujimaki, Ph.D., founder and CEO of dotData. “Whether using machine learning for product demand forecasting, customer churn, revenue recovery, or failure detection, building strong features is difficult but critical to developing accurate predictions. dotData Py Lite was created to put the power of enterprise-grade automated feature engineering on everyone’s laptop. It takes one minute to install, ten minutes to develop, and deploys instantly.”

Features and benefits of dotData Py Lite include:

  • All features and functionality of dotData’s award-winning automated feature engineering and AutoML
  • Containerized predictions from data through feature to ML scoring
  • One-minute installation on Windows, MacOS or Linux
  • Minimum resource requirements (Two CPU cores and 4GB of RAM)
  • Fully compatible with cluster-based dotData Py and dotData Enterprise deployment for scale-out

dotData Py Lite is designed to support the following three use cases:

  • Quick and affordable environment for AI and ML experiments via AI automation for those who just started their AI/ML journey or who are exploring AI automation capabilities
  • Powerful yet easy library to explore a broad range of feature hypotheses via automated feature engineering for data scientists
  • Simple and portable way to deploy and productionalize E2E AI pipelines from data and feature engineering to ML scoring as AI micro-services via automated containerization for IT and engineering teams

The company’s data science automation platform automates feature engineering, the most manual and time-consuming step in AI and ML projects. dotData’s proprietary AI technology automatically discovers hidden patterns behind hundreds of tables with complex relationships and billions of rows and AI-features for AI and ML algorithms.

Until now, says the company, feature engineering has 100 percent relied on intuition and experience of domain experts and data scientists; with dotData, users can leverage AI to discover unknown-unknowns and build greater AI and ML models. Experienced data science teams can leverage dotData’s AI features to augment in-house developed features.

Automated feature engineering (AutoFE) provides a fast and automated means to rapidly prototype use cases, explore new datasets to find important patterns, and improve accuracy of AI and ML models, says the company. It is available as a Python library seamlessly integrated with a user’s existing Python workflow, and cuts 80 percent of time to develop features for AI and ML models.

Business intelligence and analytics teams can leverage the company’s no-code AI/ML automation solution to make their reporting and dashboards more predictive and actionable. It offers a streamlined integration of AutoFE and automated machine learning (AutoML) and allows users to develop production-ready features and ML models from raw business data, in just days.


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