Alteryx adds data science operationalizing functionality, based on technology from Brooklyn-based Yhat, which it acquired in June.
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Predictive analytics, prescriptive analytics, machine learning and AI are gaining in mindshare and adoption. The next frontier? Making them accessible to business users and embedding them into business applications.
PitchBook, a purveyor of private equity market data, has now integrated data from the public markets, sourced from Morningstar, its parent company. The companion data feeds and APIs from the PitchBook Platform provide promising fodder for AI-driven investing.
Hallmarks of Anaconda's new Enterprise release include deployment of Python-generated assets to executives and analysts, and Python machine learning models to mainstream developers.
Microsoft is joining the Databricks-backed MLflow project for machine learning experiment management. Already present in Azure Databricks, a fully managed version of MLflow will be added to Azure Machine Learning and made available soon.
.NET developers, across platforms, now have access to machine learning from their home turf. Microsoft Automated Machine Leaning (AutoML) is included, and a Model Builder extension for Visual Studio rolls out an ML red carpet for developers.
The company founded by New York Times best-selling author Randi Zuckerberg sees a place for STEM and AI in the restaurant industry. It also believes such a venture can bring tech to smaller communities.
Once a niche technology, Automated Machine learning (AutoML) is now a thing. Helping non-data scientists do simple AI, and helping trained data scientists do complex work ever-faster, AutoML technology is catching on, and may well put AI in the Enterprise fast lane.
SAP is embedding AI in applications; MapR is doing so in its data platform. In both cases, AI is becoming more ubiquitous and more convenient.
Using machine learning, along with basic information and history about customers, health insurance carriers can up their game.