What can you expect from Machine Learning as a service platform?

Tiara Williamson
Tiara WilliamsonAnswered

The rise of Machine Learning related services doesn’t show signs of dwindling. In fact, AI integrations in businesses worldwide has accelerated the need for development in this sector. In light of this , most companies are striving to offer a high-quality  Machine Learning platform as a service (ML PaaS) option(/s) for their clients and customers. ML PaaS is the fastest growing service branch in the domain of the public cloud. One of the main reasons for this is that this type of service platform delivers highly appreciated units for data scientists and developers model management and development of iterative software.
If you are a developer, you will enjoy the advantages of data processing pipelines for ETL tasks automation. Publishing the latest version of a model is unencumbered with deploying and packaging the dependencies and artifacts. With the help of a few APIs, you can propel a large cluster of GPU-based machines fully configured with monitoring tools, training frameworks, and data preparation tools that are ready to start operating and doing more complex tasks. Software Development Kit (SDK) simplified the processing of the data and software delivery pipelines for developers.
It’s simple to switch between CPU training clusters and GPUs running on the latest versions of accelerators by changing just one single parameter. The market of public cloud platforms is also rocketly integrating AI-supported services into their operations and products. Public cloud Machine Learning platforms are in high demand, and AI giants like Google, Amazon, Microsoft, and IBM are actively taking part in that trend. They have already developed powerful and attractive Machine Learning PaaS options and services for their clients and education sources regarding this type of platform usage and development so feel free to investigate further and find the one that fits the needs of your business or project.

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