Machine learning
Machine learning holds immense potential like no other analytical method. As a sub-discipline of AI, it enables you to extract valuable insights and knowledge from both existing and new data. Enhance future predictions and actionable recommendations by developing your own machine learning models, leveraging individual or pre-existing algorithms, all on the IONOS Cloud.
Example: Offer your customers a significantly improved user experience with purchase suggestions and customized information.
In the machine learning lifecycle, two distinct phases exist: development and training, and inference or operational.
During the development and training phase, the data scientist builds the machine learning model using training data. Numerous tests and algorithm refinements are performed to ensure its accuracy. In the subsequent inference phase, machine learning engineers convert the model into a pipeline for specific tasks.
For developing and deploying the pipeline, a range of cloud products and open source tools are utilized:
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