Developers are not the kingmakers of the fastest growing area of technology — machine learning (ML) and artificial intelligence (AI). Although TensorFlow, Sckit-Learn and Spark MLLib are popular on GitHub, they are at their core libraries used by data scientists to build models that enable machine learning and types of artificial intelligence functionality.
In fact, 51 percent of those doing ML said their models are created by internal data science teams, according to a recent O’Reilly survey. From the perspective of professionals that are creating data products, using ML services from a cloud provider is almost never even a consideration. Yet, AI/ML as a service, perhaps accessed via an API, is often pitched as the primary way developers will get involved in this field.
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