AWS 机器学习能力合作伙伴具备在 AWS Cloud 中交付机器学习(ML)解决方案方面的专业知识。这些合作伙伴提供一系列服务和技术,帮助您创建智能的业务解决方案,从启用数据科学工作流到使用机器智能增强应用程序。
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提供数据处理,例如摄取、合并、删除重复记录、缺失值插补、扩缩/标准化数据值、删除相关特征、特征工程等。
用于机器学习的无代码平台和低代码平台,通常以可视化界面为主,支持端到端模型开发。
高级代码解决方案、RESTful API、GraphQL 和算法,让客户可以访问经过训练的模型和用于训练模型的组件。
AWS 机器学习能力合作伙伴具备专业知识,能帮助组织解决人工智能中最具挑战性的难题,包括数据工程、数据科学、机器和深度学习以及大规模推理的生产部署。
开发、部署和维护机器学习应用程序,这些应用程序可对客户的业务成果产生积极影响、增加 AWS 服务(特别是 AWS AI 服务)的价值,以满足特定的客户需求。
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探索 AWS 机器学习能力合作伙伴电子书、网络研讨会、客户成功案例等。
机器学习基础知识
观看点播网络研讨会,了解这些技术对数字化转型的重要性。
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Financial Services
Paynela Improves Data Accessibility Using generative AI With the Help of Mission
United StatesPaynela, a Puerto Rico-based healthcare financing innovator, revolutionized patient financial assistance through cutting-edge solutions powered by AWS Partner Mission. Dedicated to making healthcare more accessible, Paynela helps patients manage their out-of-pocket medical expenses with dignity and ease. By leveraging Amazon Web Services (AWS) and Mission's expertise, Paynela harnessed the power of generative AI to analyze complex healthcare data, resulting in deeper insights and expanded patient support capabilities.
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Software & Internet
NeuralSpace Accelerates AI Model Training Speed by 96% in Migration to AWS with Rebura
United KingdomNeuralSpace, a London-based AI startup, had the same problem that many startups have: not enough time, not enough money, and too much to do. It needed to develop and train the AI models that powered its language AI applications—automatic translation of text and speech, automated subtitling, and automated AI dubbing of content—but these processes were taking too long. With 20–30 TB of data being used to train each model, it could take 3–6 months to train just one. And the company needed to train multiple models to develop its products. NeuralSpace knew that it needed to find a way to speed up model training that would fit within its limited budget. With the help of AWS Partner Rebura, NeuralSpace migrated to Amazon Web Services (AWS) to enable faster modeling and a crucial pivot in focus.
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Manufacturing
Usiminas, with Enkel’s Support, Reduces R$ 9 Million in Transportation Costs by Optimizing Processes Through AWS Services
BrazilUsiminas, supported by AWS Partner Enkel tackled significant challenges in freight pricing and route optimization within the steel industry. By developing a customized automation platform based on AWS services, the Brazilian steel company streamlined logistics processes, leading to a 14% reduction in costs and significant efficiency gains. The project not only cut delivery distances by 448,000 kilometers but also resulted in a notable decrease in CO2 emissions, avoiding the release of 1,577 metric tons. This project enhances Usiminas' market competitiveness and reinforces its commitment to environmental sustainability, demonstrating the positive impact of innovative solutions in the logistics sector.
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Esra Kayabali, 2025-02-25随着生成式人工智能领域的不断发展,Amazon Bedrock 也在不断扩充其基础模型(FM)产品阵容。今日, [...]
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Elizabeth Fuentes, 2025-02-252 月 20 日举办的 2025 年 AWS 开发者日活动展示了如何将可靠的生成式人工智能集成到开发工作流程中 [...]
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AWS Team, 2025-02-07本文将分享我们在实际案例中利用亚马逊在re:Invent 2024刚刚推出新一代自研大模型Amazon Nova Lite构建视频分享平台的智能审核方案。我们分别从审核的准确性、处理速度、运营成本等维度深入探讨这个话题。
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AWS Team, 2025-02-25华宝新能与亚马逊科技团队合作,探索利用 Amazon Bedrock 和 GenAI 提升客户服务效率的过程。通过多阶段迭代,从 RAG 到 LLM+Workflow,再到多智能体 Agent 系统,团队逐步应对数据质量、意图识别等挑战,成功将 GenAI 应用于订单处理等复杂场景,重塑了客服团队价值定位。
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AWS Team, 2025-02-12本文介绍了亚马逊云科技作为云计算领域的领导者,通过创新的 10p10u 网络架构,为满足万卡级别 Nvidia GPU 或亚马逊自研 Trainium2 加速器的超大规模算力需求挑战提供了网络解决方案。本文详细介绍这一突破性技术的背景、设计目标和核心创新。
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