No matter your IT role, Amazon Web Services has machine learning tools and services to meet your needs. AWS machine learning tools and services are specially designed to be workable for a wide level of expertise.

ML Services are driven by API’s which means that developers can add intelligence to any application. AWS offers numerous pre-trained services that provide for chat and computer speech, vision, and even language analysis. AWS also supports all of the primary learning frameworks, including Caffe2, Apache MXNet, and Tensorflow, making it possible to bring or develop any model you want.

One of the major plusses of AWS machine learning is security. You can control access to resources with granular permission policies. AWS Storage and database services have strong encryption to make certain your data stays secure. You also benefit from the ability to choose whether you want to manage the encryption keys or let AWS manage them.

When it comes to analytics, you can choose from a broad set of data analysis services that include data warehousing, business intelligence, batch processing, and stream processing. You can even orchestrate your data workflows.

Another important feature of AWS machine learning is that the machine learning services offered are integrated deeply with the rest of the platform, including the data lake and the database tools you will need to run machine learning workloads.

Computing power is critical for machine learning. AWS provides a wide array of computing options for both training and inference for machine learning. There are powerful GPU-based instances as well as compute and memory-optimized instances. They even offer field-programmable gate arrays that allow one to create a digital integrated circuit that can be programmed after manufacturing takes place. For instance, a computer could use an FPGA to tailor a microprocessor to their own specific needs.

Amazon Sagemaker is the newest managed platform that allows developers to build, train and deploy machine learning models at scale with ease. Amazon Sagemaker removes much of the complexity that interferes with developer success with each of the steps in Machine Learning from collecting and preparing training data and discovering which elements of your data set are essential to selecting an algorithm and framework, deciding on your approach, teaching and training your model how to make predictions and finally fine-tuning your model.

From platforms to services and tools for machine learning, AWS has you covered. It is comprehensive, secure, cost-efficient and makes machine learning easy for everyone.

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Oct 12 21
Christina Zumwalt