AWS Partner Network (APN) Blog

Category: Amazon Machine Learning

BMC-AWS-Partners

How to Orchestrate a Data Pipeline on AWS with Control-M from BMC Software

In spite of the rich set of machine learning tools AWS provides, coordinating and monitoring workflows across an ML pipeline remains a complex task. Control-M by BMC Software that simplifies complex application, data, and file transfer workflows, whether on-premises, on the AWS Cloud, or across a hybrid cloud model. Walk through the architecture of a predictive maintenance system we developed to simplify the complex orchestration steps in a machine learning pipeline used to reduce downtime and costs for a trucking company.

Read More
Machine Learning-4

How to Use Amazon SageMaker to Improve Machine Learning Models for Data Analysis

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.

Read More

How Steamhaus Used AWS Well-Architected to Improve Sperry Rail’s Artificial Intelligence System

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.

Read More
Machine Learning-3

Gathering Market Intelligence from the Web Using Cloud-Based AI and ML Techniques

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.

Read More

Sponsoring Amazon re:MARS 2020 Can Help Grow Your Artificial Intelligence Business

Amazon re:MARS 2020 is our second annual artificial intelligence event, covering a diverse array of topics and themes related to machine learning, automation, robotics, and space (MARS). The event brings together innovative minds to share new ideas across these rapidly advancing domains. APN Partner are invited to join us as a sponsor at Amazon re:MARS and gain access to decision makers who are starting or accelerating MARS tech initiatives.

Read More
Deloitte-TrueVoice-Logo-5

Unlocking the Value of Your Contact Center Data with TrueVoice Speech Analytics from Deloitte

Voice data represents a rich and relatively untapped source of information that can help organizations gaining precious insights into their customers and operations. By leveraging a number of AWS services, Deloitte’s speech analytics solution, TrueVoice, can process voice data at scale, apply machine learning models to extract valuable information for this unstructured data, and continuously refine and enrich such models, tailoring them to specific industries and business needs.

Read More
Deep-Instinct_AWS-Competency

How Deep Neural Networks Built on AWS Can Help Predict and Prevent Security Threats

Deep learning is inspired by the human brain and once a brain learns to identify an object, its identification becomes second nature. Similarly, as Deep Instinct’s artificial neural network learns to detect more and more types of cyber threats, its prediction capabilities become instinctive. As a result, malware both known and new can be predicted and prevented in zero-time. Deep Instinct’s predictive threat prevention platform can be applied against known or unknown threats, whether it be a file or fileless attack.

Read More
TensorIoT_AWS Solutions

Bringing Intelligence to Industrial Manufacturing Through AWS IoT and Machine Learning

With connected IoT solutions built on AWS, businesses can be more proactive with maintenance instead of reactionary, allowing them to fix problems with machinery before they become critical. Reliance Steel & Aluminum Co. teamed up with TensorIoT to solve for this use case. Together, they built an IoT solution on AWS that ensures the maintenance needs of Reliance’s industrial machinery are anticipated and that machines can be serviced before breaking down.

Read More

How to Use Amazon Rekognition on Cloudinary to Auto-Tag Faces with Names

Learn how to seamlessly integrate Amazon Rekognition with the Cloudinary platform, and build an application that automatically tags people in images with names. This solution learns people’s faces from photos uploaded to a “training” folder in Cloudinary. In many cases, a single photo of someone is enough for Amazon Rekognition to learn and then, later on, identify and tag that person. This works in most photograph scenes and even pictures with many other people in them.

Read More
Healthcare-1

How to Use Amazon Rekognition and Amazon Comprehend Medical to Get the Most Out of Medical Imaging Data in Research

Medical imaging is a key part of patient health records and clinical trial workflows. Many facilities still burn medical imaging on CDs, a time-consuming and error-prone process. Ambra Health’s automatic pixel de-identification feature uses Amazon Rekognition and Amazon Comprehend Medical APIs to allow customers to de-identify images and reduce error. Now, it’s easier than ever to deploy an integrated application fabric that elevates healthcare efficiency and care.

Read More