AWS Partner Network (APN) Blog

Tag: Machine Learning

NVIDIA-APN-Blog-110822

Privacy-Preserving Federated Learning on AWS with NVIDIA FLARE

Federated learning (FL) addresses the need of preserving privacy while having access to large datasets for machine learning model training. The NVIDIA FLARE (which stands for Federated Learning Application Runtime Environment) platform provides an open-source Python SDK for collaborative computation and offers privacy-preserving FL workflows at scale. NVIDIA is an AWS Competency Partner that has pioneered accelerated computing to tackle challenges in AI and computer graphics.

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Explore Key Themes in the AWS Machine Learning Visionaries Partners Report

The AWS Machine Learning Visionaries Partners Report is a quarterly series that tracks, selects, collates, and distributes horizontal technology capabilities enabled by machine learning in areas that AWS expects to be transformative in 1-3 years. The series’ purpose is to share our insights with AWS Partners and to collect their interest, expertise, and insights in co-building along these prioritized themes. The reports include updates on series topics as we see changes in those areas, and new topics will also be added.

ElectrifAi-APN-Blog-110222

Fast, Accurate, Alternate Credit Decisioning Using ElectrifAi’s Machine Learning Solution on AWS

Infusing machine learning into core business processes such as credit scoring creates a competitive edge for banks and financial services institutions. It does not require a data science team, expertise, or platform rollout. Explore an ML-based credit-decisioning model built by ElectrifAi in collaboration with AWS whose model rapidly determines the creditworthiness of a SME, and data-driven, actionable insights reduce the overall processing cost and are consistent and free from any potential human biases.

Presidio Builds Conversational Bots Using HAQM Lex and the HAQM Chime SDK

With the rise of voice assistants like HAQM Alexa, customer expectations for handling inquiries and transactions have shifted from the outdated phone keypad, also known as dual tone multi-frequency (DTMF), to modern conversational AI that enables machines to communicate with human beings. In this post, we demonstrate how Presidio implemented conversational AI to check the wait time and reserve a table at a restaurant using HAQM Chime SDK, HAQM Lex, and HAQM Polly.

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Graph Feature Engineering with Neo4j and HAQM SageMaker

Featurization is one of the most difficult problems in machine learning. Learn how graph features engineered in Neo4j can be used in a supervised learning model trained with HAQM SageMaker. These novel graph features can improve model performance beyond what’s possible with more traditional approaches. Together, these components offer a graph platform that can be used to understand graph data and operationalize graph use cases.

HCLTech-APN-Blog-102522

Fluid CCI Leverages AWS AI/ML Capabilities to Make Today’s Contact Centers Future-Ready

A digital journey is of strategic importance for many organizations, and digital transformation enabled by cloud technologies has increased efficiency and raised productivity with improved stakeholder experiences. To achieve these outcomes, transformation initiatives need to be holistic, interlinked, and inclusive. Learn how to supercharge customer experiences and make your contact center future-ready by leveraging HCLTech’s Fluid Contact Center Intelligence (Fluid CCI) and AWS AI/ML services.

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Empowering Sustainability with the Sogeti Carbon Estimator

In line with Capgemini Group‘s sustainability vision to become a net zero business by 2040, Sogeti has collaborated with AWS to find a pragmatic solution that is helping to bring this vision to life—the Sogeti Carbon Estimator (SCE). This tool can be used to automatically bring insights into the carbon footprint of any cloud component used to serve technology, including complex AI solutions enabled by MLOps. SCE highlights the goal of many cloud providers and businesses—to unlock the value of cloud sustainably.

Say Hello

Say Hello to 108 New AWS Competency, Service Delivery, Service Ready, and MSP Partners Added in August

We are excited to highlight 108 AWS Partners that received new designations in August for our global AWS Competency, AWS Managed Service Provider (MSP), AWS Service Delivery, and AWS Service Ready programs. These designations span workload, solution, and industry, and help AWS customers identify top AWS Partners that can deliver on core business objectives. AWS Partners are focused on your success, helping customers take full advantage of the business benefits AWS has to offer.

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How the Infosys Customer Intelligence Platform Delivers a World-Class Customer Experience

Today’s customers demand personalized service. To meet these expectations, enterprises must continuously learn, evolve, and develop mechanisms to drive usability and improve the omnichannel experience. In this post, you’ll learn about the Infosys Customer Intelligence Platform (CIP), a solution built using HAQM Neptune and AWS to accelerate data ingestion, data processing, data modeling, and data analytics.

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Integrating SaaS Data Platforms from ISV Partners with AWS Services

A SaaS data platform may run in the account of an ISV or a dedicated account provided by the customer. Learn about the main AWS services SaaS data platforms can integrate with to provide customers with a seamless experience and take advantage of AWS services in order to accelerate their drive to meeting their business goals. Explore how those integrations can be built and examples of AWS ISV Partners who have successfully developed these integrations.