Preparing data with DataRobot
The first part of what the platform offers is the data preparation component. DataRobot simplifies the data preparation process by offering a range of features to streamline data ingest, cleaning, transformation, and integration. Let’s dive into these features in detail.
Ingesting data for deep learning model development
The development of deep learning models in DataRobot begins with the pivotal step of data ingestion. This process allows you to directly import your data from various sources, including cloud storage (such as AWS S3), Google Cloud Storage, local files, or databases such as PostgreSQL, Oracle, and SQL Server. The platform accepts diverse file formats, including CSV, XLSX, and ZIP files. Additionally, the platform supports image, text, document, geospatial, numerical, categorical, and summarized categorical data through secondary datasets as input data types. For the target data types, the platform supports numerical, categorical...