Machine Learning - Research (EN)

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Lor alicimi nven- tecese nulparu ntiaspi duciam fugiaepudam re omnisqu aturiti simusant ullab idist, tempost utectem ea des eritatis rerferum aceria non porrunt, conet evellaute et omnit, simenda nissimus dolentur? Quibust, utem. Qui audipsam, vellam, ut eicimus sol- orum qui aut as accabor ectibus ius esti at eos eos eiusand itat- ur aniscil ibusdae reheni cum dolest, aliciis min et periatur? Pedigenia nos ad que seque volenim aut moluptas sam sedios millest eturiorae ventiis qui quae dent eum exces doloria sse- quis aliqui voleconsequiata volum quiaeru ntiisci to et eossum omnist laboreh C U S T O M R E S E A R C H R E P O R T 6 Training and AI Services Can Help Close the Skills Gap S P O N S O R ' S V I E W P O I N T Implementing AI and machine learning throughout your organization requires a collab- orative, interdisciplinary approach among data scientists, machine learning specialists, developers, and domain experts. As you build your AI and machine learning strategy within the organization, it's critical to evaluate the skills your organization currently has and build a plan to close any gaps. At Amazon, AI and machine learning have been an integral part of the business for over 20 years. AI and machine learning enable virtually every part of our business, including real-time personalization and recommendations on Amazon.com; inventory forecast- ing; and natural language understanding with Alexa. Our goal is to put machine learning technology in the hands of every organization, including those that are still working to build the relevant skills in the workforce. Pretrained AWS AI services provide ready-made intelligence for business applications and workflows. Fully managed services such as Amazon Personalize, Forecast, Kendra, and Fraud Detector reduce machine learning complexity so you can focus on business priorities such as personalizing customer experiences, modernizing your contact center, reducing online fraud, and increasing customer engagement. These services don't re- quire deep machine learning expertise, and developers can easily get started. Boot camps, hackathons, and learning events can help accelerate the learning in your organization. Learning tools like DeepRacer, DeepLens, and DeepComposer put machine learning in the hands of every developer, allowing nonexperts to learn and build on their own. Amazon's Machine Learning University offers a variety of free courses for business decision makers, developers, and machine learning experts. Encourage your teams to leverage these great learning resources and build their own customized curricula. Iden- tifying a few key AI and machine learning champions within your team and establishing a center of excellence will help build a virtuous talent cycle through continuous learning. Amazon's Machine Learning Embark program can also help accelerate your machine learning journey. Embark pairs your team with Amazon experts to prepare data, build and train models, and put models into production. It combines hands-on educational workshops with brainstorming sessions and advisory professional services to help you identify machine learning solutions to business challenges and then go step-by-step through the process of development. Finally, our extensive network of AWS Machine Learning Competency Partners offers a range of services and technologies to help you create intelligent solutions for your busi- ness. Leading companies work with these partners to innovate with machine learning on AWS. These partners can help you start realizing business value while you build skills within your organization. Learn more at aws.ai. About Amazon Web Services AWS offers the broadest and deepest set of machine learning and Al services. On behalf of our customers, we are focused on solving some of the toughest challenges that hold back machine learning from being in the hands of every developer. Tens of thousands of customers are already using AWS for their machine learning efforts. You can choose from fully managed Al services for computer vision, language, recommendations, forecasting, fraud detection, and search; or Amazon SageMaker to quickly build, train, and deploy machine learning models at scale. SageMaker Studio offers the first fully integrated development environ- ment for machine learning. You can also build custom models with support for all of the popular open-source frameworks. Our capabilities are built on the most comprehensive cloud platform, optimized for machine learning with high-performance computing and no compromises on security and analytics. Learn more at aws.ai. MIT SMR CONNECTIONS MANAGER'S GUIDE — TRANSFORM YOUR WORKFORCE WITH SKILLS FOR MACHINE LE ARNING

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