Tag: Machine Learning

The AWS Competency Program welcomed 47 new APN Partners in September—spanning workload, solution, and industry designations. The AWS Competency Program helps customers identify and choose the world’s top APN Partners that have demonstrated technical proficiency and proven customer success in specialized solution areas. Please join us in welcoming our newest AWS Competency Partners!

The AWS Competency Program welcomed 20 new APN Partners in August—spanning workload, solution, and industry designations. The AWS Competency Program helps customers identify and choose the world’s top APN Partners that have demonstrated technical proficiency and proven customer success in specialized solution areas. Please join us in welcoming our newest AWS Competency Partners!

AWS provides a broad set of managed services for data analytics that, along with a strong APN Partner community, can help you build a scalable, secure, and cost-effective data lake. Customers and APN Partners want to know how to put all these pieces so we created a new poster and video explaining the overall flow of data—from data collection, storage, and processing all the way to analytics and machine learning.

While market adoption of machine learning varies across industry segments, healthcare and life sciences have lots of opportunity to explore. Pharmaceutical and biotech industries, specifically, have low utilization of the large volumes of data they collect and store for regulatory purposes. Aizon is an AWS Partner that offers a number of ML solutions to enhance utilization and management of such data in a way that adheres to Good Manufacturing Practice (GMP) in the cloud.

Join us for the inaugural APN Digital Summit, a virtual webinar series for our APN Partner community. Hear from AWS team experts and get your questions answered at one of our 19 virtual sessions. We have webinars available for all APN Partner types, so take a look at our full agenda, which includes topics on AWS Serverless, AWS Storage Solutions, Amazon GuardDuty, Data Lakes, and Machine Learning.

H2O is an open source data machine learning platform that provides a flexible, user-friendly tool to help data scientists and machine learning practitioners. It was created by H2O.ai, an APN Advanced Partner with the AWS Machine Learning Competency. In this post, we look at setting up an H2O cluster, import data from Amazon S3, create an AWS Lambda deployment package from the model, and finally deploy a RESTful endpoint. Following these steps, you can migrate your H2O Flows to AWS in about 10 minutes.

The APN Navigate Program provides a prescriptive path for APN Partners to build a specialized practice on AWS and deploy innovative solutions on behalf of customers. We have Navigate tracks for Blockchain, Contact Center, Database Services, DevOps, End User Computing, Financial Services, High-Performance Computing, IoT, Machine Learning, Microsoft Workloads, Migration, Serverless, SAP on AWS, VMware Cloud on AWS, and the AWS Managed Service Provider (MSP) Partner Program.

At the AWS London Summit, we announced the new AWS Machine Learning Competency Program for APN Consulting Partners. Launch Partners in this program have deep expertise and proven customer success in Machine Learning on AWS, and we are excited to showcase some of their stories. The AWS Competency Program helps customers identify and choose the top APN Partner for their AWS projects and workloads.

We are often asked how to integrate software with Amazon SageMaker and use the service’s built-in machine learning algorithms. In this post, we discuss how to use the training capabilities of Amazon SageMaker to leverage its built-in algorithms. The types of applications that can integrate with Amazon SageMaker are data science platforms, business intelligence tools, or any application that needs to use machine learning behind the scenes.

AWS Solution Space allows AWS Competency Partners to showcase customer-ready solutions based on architectures validated by AWS. These are quick, cost effective, repeatable solutions meant to create new business leading to production workloads. Customers can also request AWS support for launching each solution. At launch, we are featuring 10 customer-ready solutions: 5 for Big Data, 3 for Machine Learning, one for Security, and one for End User Computing.