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Building, tuning and deploying models has never been this easy.
DataRobot gives you access to hundreds of the latest machine learning algorithms, with full transparency and control over the model building and deployment process. Tap into the best practices of Kaggle-ranked data scientists to automate the data pre-processing, feature engineering, and parallel model building process. Then, use your data science knowledge and domain expertise to find the best solution for your project and put it into production with just a few lines of code.
Providing Business ValueDataRobot has been designed to help data scientists wring value from every project. With an emphasis on supporting techniques like supervised machine learning and transfer learning, the platform also includes features that ensure business value like profit curves, prediction explanations, and one-click deployment with governance. All of this is integrated with automation to ensure your time is spent providing business value.
DataRobot carefully curates and validates algorithms from R, Python, Spark, TensorFlow, and other sources. We spend thousands of hours analyzing what Kaggle techniques hold up. Then, our machine learning engineers incorporate these techniques, while ensuring they run quickly, scale to large datasets and catch edge cases like missing values and new levels. Finally, we continually run thousands of automated tests to ensure our models are reliable.
DataRobot starts by letting you select which model you want to deploy from hundreds of possibilities. With the powerful DataRobot API, you can immediately put any model into production with just a few lines of code, regardless of whether you need real-time predictions, batch deployments, or scoring on Hadoop. Update your models with no downtime and easily build continual learning pipelines.
Solving the Hardest Data Science ProblemsWhether you are trying to forecast sales for a million products or working with extremely wide genomic data, DataRobot is capable of solving the hardest data science problems. Using our API, data scientists will often build hundreds or thousands of models to solve problems, all of which is easily done with our R and Python clients designed for data scientists.