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Data science platforms News
June 24, 2019
Tellius is now part of the Google Cloud Partner Program, which enables it to integrate with Google BigQuery and Google Analytics in addition to using the Google Cloud Platform.
June 20, 2019
DataRobot machine learning tools should see a boost following the company's acquisition of ParallelM, a startup with tools for deploying, managing and monitoring AI.
May 13, 2019
Speedy deployment of machine learning jobs may not arrive too soon. But container platform enhancements from Red Hat aim to quicken the uptake of such innovations.
April 25, 2019
Databricks' MLflow gets support from Microsoft and new features, including easier model tracking, as the open source tool prepares for its 1.0 release next month.
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Neural network uses are starting to emerge in the enterprise. This handbook examines the growing number of businesses reporting gains from implementing this technology. Continue Reading
This handbook offers advice on choosing machine learning platforms and using them to get accurate and meaningful information from analytics applications. Continue Reading
Data science platforms include a variety of technologies for machine learning and other advanced analytics uses. This handbook examines them and how they can be used. Continue Reading
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Deep learning and neural networks are picking up steam in applications like self-driving cars, radiology image processing, supply chain monitoring and cybersecurity threat detection. Continue Reading
Before autoML can improve model building and deployment, enterprises need to choose a platform. Here, we evaluate autoML platforms by category, key features and accessibility. Continue Reading
To reach full analytics potential, machine learning platforms powered by AI must provide scalability, handle multiple models, integrate with data sources and be cloud-friendly. Continue Reading
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The relationship between data scientists and companies using AI is evolving rapidly, shifting from a focus on trained professionals to experienced employees with automated tools. Continue Reading
Enterprises have long seen the value of predictive analytics, but now that AI is starting to influence forecasting tools, the benefits may start to go even deeper. Continue Reading
AI security hasn't been the top concern of most data scientists using machine learning. But as these systems move closer to the core of the business, security is becoming critical. Continue Reading
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Most data science projects end up facing similar problems, such as lack of robustness and data quality issues. In this feature, experts offer tips on how to overcome these challenges. Continue Reading
To create his March Madness bracket predictions, the head of data science at DataRobot uses a host of machine learning algorithms and some predictive analytics. Continue Reading