Machine Learning with Amazon SageMaker, algorithms and frameworks


Amazon was recently at the Chicago Summit 2018 and one of the keynotes was about machine learning (ML) with Amazon SageMaker, focusing on algorithms and frameworks.

Led by Kumar Venkateswar, senior product manager at AWS, the rather lengthy keynote focuses on algorithms and frameworks, which form a fundamental part of machine learning (ML).

Some of the most commonly used algorithms and frameworks are already built-in with Amazon SageMaker, making ML easier to address some of the details use cases.

The session is all about these built-in algorithms and frameworks as well as how these can be used for ML models. The session also talked about the flexibility of using custom algorithms depending on the need as well as touched plenty of other subjects.

Amazon was a big part of the Chicago Summit 2018, talking about different subjects like building intelligent apps with Amazon ML and its language services, how to accelerate machine learning with SageMaker, how to create advanced text analytics solution with NLP, or precisely AMazon Comprehend or Amazon RDS, Elasticsearch Service and/or Amazon Neptune.


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Slobodan Simic is foremost an IT enthusiast who discovered his knack for writing, which lead to becoming both an IT journalist and later an Editor for a number of publications. He has been covering anything from the consumer- and professional-oriented hardware to software markets and networks. With a focus on chasing down leads, making sure that fresh content is ready for publishing, as well as keeping up with the evergrowing and evolving IT world, writing has become more of his passion rather than just a job.