At DataRobot, we strive to help enterprises uncover hidden predictive insights through automated machine learning. As technologies like IoT and mobile become more prevalent, vast amounts of new data (in a host of formats) become available. The demand for data from analysts, data scientists, and executives is growing exponentially as more challenging business problems are being addressed. Given the growth…
Why Machine Learning Is So Hard The machine learning process can be challenging for developers, data engineers, and data scientists — building, training, and then deploying models into production is complicated and time-consuming. First, you need to collect and prepare historical training data where you know the outcome you are trying to predict, which will be used to discover which…
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CRN recently published its annual list of Emerging Vendors, celebrating startups and notable companies that are driving major innovation and change within the IT industry. There are seven categories in the Emerging Vendors list – Cloud, Data Center, Security, Big Data, Unified Communications, Internet of Things (IoT), and Storage – and the list serves as a valuable resource for solution…
Many organizations are looking for ways to apply AI and analytics to their business, which requires attention all the way from data prep to machine learning to deployment. At DataRobot, we're pleased to announce our partnership with Databricks, which allows us to provide companies with a robust solution to accelerate their analytics innovation and building of AI applications. Founded by…
You want to use Alteryx, the leading tool for data preparation. And you want to use DataRobot for automated machine learning and model deployment. You can do both with DataRobot Connectors for Alteryx, available as a free download from the Predictive District inside the Alteryx Analytics Gallery. Alteryx users can insert these two powerful DataRobot Connectors directly into Alteryx workflows:…
Today’s Artificial Intelligence (AI) solutions projects require a lot of collaboration and teamwork in order to grow and succeed. However, limited resources — such as not having enough available and skilled data scientists and tools that don’t offer high levels of automation — are hampering even the best teams out there. This is the moment when partnerships and collaborations step in…