Dato, creator of the popular machine learning platform GraphLab Create, announced today toolkits and training for developers building Intelligent Applications. Developers can use Dato Toolkits to build software that leverages machine learning technology, combining historical data and real time user interaction to make predictions and decisions. The toolkits allow developers to add recommendations, sentiment analysis, churn prediction and deep to create Intelligent Applications, delivering rich and adaptive experiences to users.
Dato also announced a partnership with Coursera and the University of Washington to deliver a six-course machine learning curriculum. The partnership addresses widespread demand for the machine learning developer capabilities needed to build Intelligent Applications.
Over the next five years, every disruptive business will be differentiated by the intelligence of their applications. Machine learning is the core technology to make such intelligence happen,” said Carlos Guestrin, Dato co-founder, CEO and Amazon Professor of Machine Learning at the University of Washington. “We see a huge number of developers adding machine learning to their applications using the Dato platform, which is really exciting for us. Recommendation engines, sentiment analysis, churn prediction and deep learning are some of the most sought after machine learning technologies that help companies like Pandora, Zillow and StumbleUpon create new personalized customer experiences in real time.”
Dato Machine Learning Toolkits
- Recommendation engines can be added to applications to personalize user experiences by mining patterns in purchase and activity history, matching users’ tastes and predicting future purchases or interests. Examples include Pandora, MagazineLuiza and StumbleUpon.
- Image search and feature extraction using deep learning can be used to create more intuitive search experiences, automatically tag photos and improve application performance by using highly predictive features extracted from images. Examples include Compology, Beeva and Zillow.
- Churn prediction detects which customers are likely to cancel a subscription or service by using advanced analytics to detect specific patterns. It can be added to applications to identify which customers are at risk of “churning.” Examples include PayPal and Nuiku.
- Sentiment analysis uses natural language processing, text analysis and computational linguistics to identify and extract subjective information in source materials. The technology can be used to discover the tone of a post in support forums or a customer’s opinion of a brand or product in reviews for better targeting. Examples include Nook, Cisco and Moodly.
Dato also announced a partnership with the University of Washington and Coursera, a leading provider of online classes, to deliver a comprehensive Machine Learning specialization. Participants can master machine learning fundamentals in six hands-on courses using the Dato platform. The course explains how to apply machine learning techniques to large and complex datasets, build applications that can make predictions from data, and create systems that adapt and improve over time.
Pricing and availability
Dato GraphLab Create subscriptions include access to the toolkits. Developers can download a free 30 days evaluation trial at www.dato.com with long term monthly pricing starting at $399. Coursera machine learning training is available through Coursera with prices starting at $79.
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