According to Databricks, batch deployment is the most common way of deploying machine learning models, accounting for approximately 80-90% of all deployments. This means running predictions from a model and saving them for later use. For live serving, results are saved to a low-latency database that will serve the predictions quickly. Alternatively, predictions can be stored in less performant data stores.
Manager
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse felis sem, interdum vitae dignissim non, tempus nec felis. Duis vulputate convallis velit eget volutpat. Sed euismod ornare metus ac efficitur. Vestibulum tempor aliquet maximus. Fusce vitae nunc consectetur mi tempor hendrerit ut sit amet ante. Aliquam eget ex non lectus accumsan fringilla. Etiam est est, interdum in porttitor vitae, facilisis vel dolor. Sed ultrices lobortis justo, in dapibus orci sollicitudin non.
Contact
