Overview
Product Information on Amazon SageMaker AI
What is Amazon SageMaker AI?
Amazon SageMaker AI Pricing
Overall experience with Amazon SageMaker AI
“大規模計算リソースの手軽な利用とエンドポイント設計の難しさ”
“Fine tuning is key and think about custom UIs for user feedback of the model and other ways to track feedback. ”
About Company
Company Description
Amazon Web Services (AWS), established in 2006, is focused on providing essential infrastructure services to businesses globally in the form of cloud computing. The key advantage offered through cloud computing, particularly via AWS, is its capacity to shift fixed infrastructure expenses into flexible costs. Businesses have been able to forgo extensive planning and procurement of servers and other Information Technology (IT) resources, owing to AWS. AWS seeks to provide businesses with prompt and cost-effective access to resources using Amazon's expertise and economies of scale, as and when their business requires. Currently, AWS offers a robust, scalable, economic infrastructure platform on the cloud powering an extensive array of businesses worldwide. It operates across numerous industries with data center locations in various parts of the globe including U.S., Europe, Singapore, and Japan.
Company Details
Key Insights
A Snapshot of What Matters - Based on Validated User Reviews
User Sentiment About Amazon SageMaker AI
Reviewer Insights for: Amazon SageMaker AI
Deciding Factors: Amazon SageMaker AI Vs. Market Average
Performance of Amazon SageMaker AI Across Market Features
Amazon SageMaker AI Likes & Dislikes
It offers end to end ML workflow support from data labelling to network , training ML jobs to model tuning, scalability is something that is very helpful for small as well as big pipelines and models and the integration with other AWS makes the monitoring easy.
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Difficulty in getting it initially setup due to slowness in our organization. Not directly related to your product, more related to service confifguration.
Read Full ReviewCost complexity is something to look out for as the cost can be very tricky when dealing with long runbook instances and large scale training models, it is restrictive to aws which can be very difficult if someone is looking to integrate with other resources apart from aws.
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Peer Discussions
Amazon SageMaker AI Reviews and Ratings
- Research and Development Manager10B+ USDManufacturingReview Source
大規模計算リソースの手軽な利用とエンドポイント設計の難しさ
機械学習を大規模にかけたいが、常にマシーンコストを支払いたくない、そのニーズにマッチしてると思うし、何より手軽に始めれられる - CLOUD ENGINEER / CLOUD SPECIALIST50M-1B USDBankingReview Source
Sagemake AI : an end to end ML workflow service
Sagemaker is an excellent service especially for enterprise and regulated environments, extremely helpful to build, train, tune and deploy AI & ML models very quickly and efficiently. - IT SERVICES ASSOCIATE50M-1B USDIT ServicesReview Source
Amazon SageMaker: A Powerful End-to-End ML Platform Built for Scale and Speed
My overall experience with Amazon SageMaker has been positive. Amazon SageMaker offers a powerful, end-to-end ML platform with strong AWS integration. It’s great for scalable projects but can be complex and costly for smaller teams. - Head of IT Services<50M USDIT ServicesReview Source
利便性高いがスポット利用時のインスタンス起動失敗を経験
全体的な利便性やスケーラビリティには満足していますが、まれにスポットインスタンスが起動できないことがありジョブが実行できないことがあるのが難点 - Engineering Manager1B-10B USDManufacturingReview Source
幅広いAIフレームワーク対応と容易なPoC実装が特徴のサービス
私の知っている範囲では製品としての実装した経験はないが、PoCとして本サービスを使わせていただき、簡単にAIアプリケーションが実装できた