In-database machine learning is built into Vertica’s core. From data exploration through data enhancement, feature filtering through algorithm training and management – the entire workflow can be done with parallel distributed performance while keeping data secure and avoiding the costs of data movement. Increase accuracy by training on full data sets. Turn predictive analytics projects from experiments to profit boosters faster with SQL productivity and an easy path to production.
Vertica’s in-database machine learning supports the entire predictive analytics process with massively parallel processing and a familiar SQL interface, allowing data scientists and analysts to embrace the power of Big Data and accelerate business outcomes with no limits and no compromises.
Want to know the latest in machine learning model development, data preparation, regression algorithms, clustering algorithms and more? Check out the newly launched Digital Learning course: Predictive Analytics Using Machine Learning. This 4-hour course, consisting of 6 self-paced modules, is designed with both new and experienced users in mind.
Are you interested in a technical deep-dive on Vertica’s built-in machine learning? Here is a paper, written by Vertica’s Chief Architect and Engineering leaders, that describes our distributed machine learning subsystem within the Vertica database. It includes Vertica’s current SQL machine learning functionalities that cover a complete data science workflow as well as model management.