Reimagine the data science experience as an open experience with this IDE, which aims to facilitate a full range of development tasks, from data acquisition and data mining to prototyping and programming. When you do, discover how you can use Apache Spark and R to pursue open analytics by building
Machine learning is finding its way into a variety of applications. Discover an open source machine learning platform that combines the data processing power of Spark with powerful machine learning algorithms courtesy of the H2O platform to tackle challenges technologists face when applying machine
Flight delays because of weather are inevitable for frequent flyers and infrequent travelers alike. Fortunately, we are living in an era in which applications such as the flight predictor app can be quickly and cost-effectively designed, built and tested to stay abreast of useful information for
Advanced analytics can help law enforcement officials across jurisdictions assist one another in predicting and preventing criminal activity. In particular, analysts, investigators and detectives can collaborate to share information to help detect threats and identify criminals.
Use open-source tools to supercharge the data science lifecycle, giving data science teams a boost as they work to provide compelling results in the complex team environments that mark modern corporations. Learn how you can make open data science an ongoing part of your business environment when
Whether organizations want to extract customer data beyond names and addresses from unstructured data sources; pull specific dates, times or monetary amounts; predict trends from sentiment data; or engage in many other uses, text analytics is the way to go. Learn the details of text analytics, and
Data science takes collaborate teams of data scientists engaging in productive, open data development initiatives that can ensure strong workflow, governance, security and management. See why open environments are revolutionizing the data science landscape.
As Spark continues to mature into mainstream adoption in the data science community, the open data analytics stack and open source tools grow more robust, giving data scientists rich core workbenches to develop evermore innovative applications.
A growing number of businesses and industries are finding innovative ways to apply graph analytics to a variety of use-case scenarios because it affords a unique perspective on the analysis of networked entities and their relationships. Gain an understanding of how four different types of graph
Something interesting is happening, and it is causing banks and other financial services to rethink how they are doing business. Customers are embracing mobile and digital channels more and more each year, and to be successful, companies must deliver customer engagement via those channels.
Across the rail and freight logistics industries, traditional approaches to asset utilization are shifting to accommodate a data-driven and proactive future where analytics and data insights provide companies with greater returns.
By using predictive analytics, providers can use real-time data to see risk factors that previously went undetected. Armed with this information, healthcare systems can then intervene and hopefully change the course of the patient's future health.