Amazon SageMaker: Build and Deploy Machine Learning Models | Rolustech

Machine learning is the act of adapting various computer systems to keep learning from experiences, and hence become better performers. This helps industries fine-tune their processes, be it manufacturing, fault detection, image and video processing, and much more. Amazon SageMaker is a machine learning program used to build, train, and deploy these models, for any use case. Built from scratch for every type of data scientist and developer in mind, most skill levels can use the platform.

Amazon SageMaker acts as a large set of tools and features that make the machine learning process accessible for everyone. Below we will go over some of the Amazon SageMaker modules that allow for better machine learning.

Amazon SageMaker Autopilot

With SageMaker Autopilot, all you have to do is feed it a tabular data set, and it will handle the rest. It will explore the data to find different solutions, then picking the best model while giving you full visibility. You just have to deploy the model that is presented to you or make minor adjustments to it just before. This ensures that you still have some agency in producing the best model possible while it. Easily create cloud applications with this feature.

Amazon SageMaker Ground Truth

Amazon SageMaker Data Wrangler

Amazon SageMaker Model Monitor

Amazon SageMaker Clarify

You will receive generated graphs regarding predictions and issues that you can then take corrective actions on.

Amazon SageMaker Pipelines

SageMaker Pipelines lets you automate a number of these steps like data loading, transformation, and much more. The end result is you can create many models in any given week and manage large amounts of data.

AWS and Machine Learning

Get AWS SageMaker and deploy your best machine learning models!

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Originally published at on March 5, 2021.

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