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Machine Learning on AWS

Posted by Marcus Zillman

Machine Learning on AWS
https://aws.amazon.com/machine-learning/

Machine learning in the hands of every developer and data scientist. At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years. Machine learning (ML) algorithms drive many of our internal systems. It’s also core to the capabilities our customers experience – from the path optimization in our fulfillment centers, and Amazon.com’s recommendations engine, to Echo powered by Alexa, our drone initiative Prime Air, and our new retail experience Amazon Go. This is just the beginning. Our mission is to share our learnings and ML capabilities as fully managed services, and put them into the hands of every developer and data scientist. Features include: a) Machine Learning for everyone – Whether you are a data scientist, ML researcher, or developer, AWS offers machine learning services and tools tailored to meet your needs and level of expertise; b) API-driven ML services – Developers can easily add intelligence to any application with a diverse selection of pre-trained services that provide computer vision, speech, language analysis, and chatbot functionality; c) Broad framework support – AWS supports all the major machine learning frameworks, including TensorFlow, Caffe2, and Apache MXNet, so that you can bring or develop any model you choose; d) Breadth of compute options – AWS offers a broad array of compute options for training and inference with powerful GPU-based instances, compute and memory optimized instances, and even FPGAs; e) Deep platform integrations – ML services are deeply integrated with the rest of the platform including the data lake and database tools you need to run ML workloads. A data lake on AWS gives you access to the most complete platform for big data; f) Comprehensive analytics – Choose from a comprehensive set of services for data analysis including data warehousing, business intelligence, batch processing, stream processing, data workflow orchestration; g) Secure – Control access to resources with granular permission policies. Storage and database services offer strong encryption to keep your data secure. Flexible key management options allow you to choose whether you or AWS will manage the encryption keys; and h) Pay-as-you-go – Consume services as you need them and only for the period you use them. AWS pricing has no upfront fees, termination penalties, or long term contracts. The AWS Free Tier helps you get started with AWS. Machine learning requires a broad set of powerful compute options, ranging from GPUs for compute-intensive deep learning, to FPGAs for specialized hardware acceleration, to high-memory instances for running inference. Amazon EC2 provides a wide selection of instance types optimized to fit machine learning use cases. Instance types comprise varying combinations of CPU, memory, storage, and networking capacity and give you the flexibility to choose the appropriate mix of resources, whether you are training models or running inference on trained models. This will be added to Artificial Intelligence Resources 2019 Subject Tracer™. This will be added to Business Intelligence Resources Subject Tracer™. This will be added to Entrepreneurial Resources Subject Tracer™. This will be added to the tools section of Research Resources Subject Tracer™.

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