machine toolsMachine Learning

Amazon Redshift is a st, fully managed data warehouse that makes it and costeffective to analyze peytescale data using standard SQL and your existing Business Intelligence BI tools.

In order to do machine learning successfully, you not only need machine learning capabilities, but also the right data store, security, and analytics services to work together.

Amazon Connect, a call center in the cloud, is integrated with Amazon Lex to build conversational voice agents, called chatbots, that can proactively resolve and route incoming customer support calls automatically.

AWS Glue is a fully managed extract, transform, and load ETL service that makes it easy for customers to prepare and load their data for analytics. You can create and run an ETL job with a few clicks in the AWS Management Console. You simply point AWS Glue to your data stored on AWS, and AWS Glue discovers your data and stores the associated metadata in the AWS Glue Data Catalog. Once cataloged, your data is immediately searchable, queryable, and available for ETL.

Developers can easily add intelligence to any application with a erse selection of pretrained services that provide computer vision, speech, language analysis, and chatbot functionality.

AWS supports all the major machine learning frameworks, including TensorFlow, Caffe, and Apache MXNet, so that you can bring or develop any model you choose.

The Amazon ML Solutions Lab pairs your team with Amazon machine learning experts to prepare data, build and train models, and put models into production. It combines handson educational workshops with brainstorming sessions and advisory professional services to help you work backwards from business challenges, and then go stepbystep through the process of developing machine learningbased solutions. At the end of the program, you will be able to take what you have learned through the process and use it elsewhere in your organization to apply ML to business opportunities.

P instances provide up to times better performance than previousgeneration Amazon EC GPU compute instances. With up to NVIDIA Tesla V GPUs, P instances provide up to one petaflop of mixedprecision, teraflops of singleprecision, and teraflops of doubleprecision floating point performance.

AWS DeepLens is the worlds first deeplearning enabled video camera for developers. Integrated with Amazon SageMaker and many other AWS services, it allows you to get up and running with deep learning quickly and easily.

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.

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Machine learning in the hands of every developer and data scientist

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.

Our goal is to accelerate the development of innovative algorithms, publications, and source code across a wide variety of ML applications and focus areas. Selected projects receive unrestricted cash gifts and AWS credits that can be redeemed towards any of our cloud services. Recipients also benefit from training resources and have the opportunity to attend an annual research seminar at our headquarters in Seattle.

As part of Amazons commitment to bring machine learning capabilities into the hands of every developer, data scientist, and researcher, Amazon is proud to offer programs that further the creation of machine learningbased solutions.

Out of the box, DeepLens is preinstalled with an optimized version of Apache MXNet.You can run any deep learning framework on the device, including TensorFlow and Caffe.

Developed by AWS and Microsoft, Gluon provides a clear, concise API for defining machine learning models using a collection of prebuilt, optimized neural network components. Developers who are new to machine learning will find this intece more miliar to traditional code, since machine learning models can be defined and manipulated just like any other data structure. More seasoned data scientists and researchers will value the ability to build protos quickly and utilize dynamic neural network graphs for entirely new model architectures, all without sacrificing training speed.

Choose from a comprehensive set of services for data analysis including data warehousing, business intelligence, batch processing, stream processing, data workflow orchestration.

The AWS Deep Learning AMIs equip you with the infrastructure and tools to accelerate deep learning in the cloud. The AMIs are preinstalled withApache MXNet,TensorFlow,PyTorch, theMicrosoft Cognitive Toolkit CNTK,Caffe,Caffe,Theano,Torch,Gluon, andKerasto train sophisticated, custom AI models. The Deep Learning AMIs let you create managed, autoscaling clusters of GPUs for large scale training, or run inference on trained models with computeoptimized or general purpose CPU instances.

Using AWS Lambda, it is easy to customize and program AWS DeepLens. Models on DeepLens even run as part of an AWS Lambda function for st experimentation.

The AWS Machine Learning Research Awards program funds university departments, culty, PhD students, and postdocs that are conducting novel research in machine learning ML.

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Amazon S is object storage built to store and retrieve any amount of data from anywhere. It is designed to deliver . durability, and stores data for millions of applications used by market leaders in every industry. S provides comprehensive security and compliance capabilities that meet even the most stringent regulatory requirements. Amazon S is the most supported storage platform available, with the largest ecosystem of ISV solutions and systems integrator partners.

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C instances are powered by . GHz Intel Xeon Scalable processors, and allow a single core to run up to . GHz using Intel Turbo Boost Technology. C instances offer higher memory to vCPU ratio and deliver improvement in price/performance compared to C instances, and are ideal for demanding inference applications.

AWS offers a broad array of compute options for training and inference with powerful GPUbased instances, compute and memory optimized instances, and even FPGAs.

Control access to resources with granular permission policies. Storage and daase 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.

More machine learning is built on AWS than anywhere else

Amazon EC F is a compute instance with field programmable gate arrays FPGAs that you can program to create custom hardware accelerations for your machine learning applications. F instances are easy to program and come with everything you need to develop, simulate, debug, and compile your hardware acceleration code. You can reuse your designs as many times, and across as many F instances as you like.

Amazon SageMaker enables data scientists and developers to quickly and easily build, train, and deploy machine learning models with highperformance machine learning algorithms, broad framework support, and oneclick training, tuning, and inference. Amazon SageMaker has a modular architecture so that you can use any or all of its capabilities in your existing machine learning workflows.

Our intelligent services provide you with the ability to add intelligence to your applications through an API call to pretrained services rather than reinventingthewheel by developing and training your own models.

AWS EMR enables you to quickly process vast amounts of unstructured data across dynamically scalable clusters using popular frameworks like Apache Spark, Presto, Hive, and Pig.

Redshift Spectrum enables you to run Amazon Redshift SQL queries against exabytes of data in Amazon S to extend the analytic power of Amazon Redshift to query vast amounts of unstructured data in your Amazon S data lake.

AWS DeepLens allow developers of all skill levels to get started with deep learning in less than minutes through sample projects with practical, handson examples.

AWS DeepLens is a physical high definition wireless video camera, with custombuilt, onboard compute capable of running deep learning inference on sophisticated models in real time.

AWS supports every major deep learning framework to provide data scientists and developers with the most open and flexible environment.

Machine learning at AWS extends r beyond the services specifically designed to create ML applications. Many services across the platform make use of machine learning to enhance the functionality they provide to you.

Amazon Macie is a security service that uses machine learning to automatically discover, classify, and protect sensitive data in AWS. Macie provides you with dashboards and alerts that give visibility into how this data is being accessed or moved to mitigate unauthorized access or inadvertent data leaks.

Machine learning requires a broad set of powerful compute options, ranging from GPUs for computeintensive deep learning, to FPGAs for specialized hardware acceleration, to highmemory instances for running inference.Amazon ECprovides a wide selection of instance s optimized to fit machine learning use cases. Instance s 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.

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ML services are deeply integrated with the rest of the platform including the data lake and daase tools you need to run ML workloads. A data lake on AWS gives you access to the most complete platform for big data.

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

Gluon is available in Apache MXNet today, a forthcoming Microsoft Cognitive Toolkit release, and in more frameworks over time.

At Amazon, weve been investing deeply in artificial intelligence for over years. Machine learning ML algorithms drive many of our internal systems. Its also core to the capabilities our customers experience from the path optimization in our fulfillment centers, and ms 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.machine toolsMachine Learning

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