Tag: Machine Learning

Data scientists creating enterprise machine learning models to process large volumes of data spend a significant portion of their time managing the infrastructure required to process the data, rather than exploring the data and building ML models. You can reduce this overhead by running Qubole data processing tools and Amazon SageMaker. An open data lake platform, Qubole automates the administration and management of your resources on AWS.

The Next Smart video series on APN TV showcases how AWS Competency Partners are helping customers grow with AWS. Whether you’re looking for consulting services or strategic technology solutions, you’ll discover APN TV videos that show how AWS customers in similar situations have teamed up with AWS Competency Partners to drive better business and bigger results. The Next Smart video series on APN TV includes demos, interviews, success stories, and webinars featuring AWS Competency Partners.

Deploying AI solutions with ML models into production introduces new challenges. Machine Learning Operations (MLOps) has been evolving rapidly as the industry learns to marry new ML technologies and practices with incumbent software delivery systems and processes. WordStream is a SaaS company using ML capabilities to help small and mid-sized businesses get the most out of their online advertising. Learn how Slalom developed ML architecture to help WordStream productionize their machine learning efforts.

Amazon EC2 Spot Instances let you reduce costs by taking advantage of unused capacity. You can further reduce costs by using the policy-based automation in Qubole Data Platform to balance performance, cost, and SLA requirements anytime you use Spot Instances. Learn how the Qubole Data Platform optimizes your Spot usage, and how it applies policy-based automation to balance your performance, cost, and SLAs whenever you use Amazon EC2 Spot Instances.

AWS DeepRacer allows developers of all skill levels to get started with reinforcement learning, which is an advanced machine learning technique that learns very complex behaviors without requiring any labeled training data, and can make short-term decisions while optimizing for a longer term goal. Learn how Slalom created AWS DeepRacer experiences for its own workforce. The cars and tracks now regularly appear in at Slalom locations across the world as valuable internal learning events.

Amazon SageMaker provides all the components needed for machine learning in a single toolset. This allows ML models to get to production faster with much less effort and at lower cost. Learn about the data modeling process used by BizCloud Experts and the results they achieved for Neiman Marcus. Amazon SageMaker was employed to help develop and train ML algorithms for recommendation, personalization, and forecasting models that Neiman Marcus uses for data analysis and customer insights.

Over two days, Steamhaus conducted an AWS Well-Architected Review on-site with the team who designed, built, and currently manage Elmer at Sperry Rail. Elmer uses machine intelligence to inspect thousands of miles of ultrasound scans collected by Sperry’s inspection vehicles, searching for evidence of cracks in the rail. This partnership allowed quick improvements in efficiency, while ensuring the requirements of running the business day-to-day did not get in the way of improving Elmer.

Many organizations face the challenge of gathering market intelligence on new product and platform announcements made by their partners and competitors—and doing so in a timely fashion. Harnessing these insights quickly can help businesses react to specific industry trends and fuel innovative products and offerings inside their own company.Learn how Accenture helped a customer use AWS to gather critical insights along with key signals and trends from the web using AI and ML techniques.

To receive the AWS Competency designation, which showcases top APN Partners to customers, organizations must undergo rigorous technical validation. To help APN Technology Partners understand this process and our validation requirements, we are releasing new versions of the AWS Competency Validation Checklists (VCL). These checklists outline the customer case study and technical criteria needed for APN Technology Partners to achieve the AWS Competency designation.

We are excited to highlight 34 APN Partners that received new designations in January for our global AWS Competency, AWS Managed Service Provider (MSP), and AWS Service Delivery programs. These designations span workload, solution, and industry, and help AWS customers identify top APN Partners that can deliver on core business objectives. APN Partners are focused on your success, helping customers take full advantage of the business benefits AWS has to offer.