APN Machine Learning Spotlight

Learn how APN Partners are using machine learning technology to drive business solutions for AWS customers.

Machine Learning Stories

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Royal FloraHolland & Xebia

Royal FloraHolland, the world’s largest flower auction company, needed to go digital, create IT infrastructure, and become more data-driven. The company engaged Xebia to help build a data science program internally and begin to develop machine learning tooling and applications.

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TINE & Crayon

TINE is a Norwegian cooperative owned by farmers that’s creating new ways to combine technology, animal science, and age-old knowledge to create better dairy products. TINE engaged with Crayon to help improve its insights, predictions, and analyses using ML on AWS.

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LinkSquares & SFL Scientific

LinkSquares provides an automated, software-based solution to streamline post-signature contract analysis. The company needed to optimize its existing solution in order to conduct contract analysis efficiently and accurately at scale. The team engaged with SFL Scientific to build a custom machine learning solution.

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Citibot & TensorIoT

Citibot’s mission is to fundamentally change how citizens contact and interact with their local governments through digital channels. After launching the initial version of the Citibot chatbot, the organization engaged with TensorIoT to improve its natural language processing.

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Lenovo & DataRobot

Lenovo is dedicated to transforming its customers’ experiences with technology through relentless innovation and a broad range of connected devices. Brazil is a primary emerging market for Lenovo and the company sought to use machine learning (ML) tools to help predict sell-out volumes in the country.

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Rue Gilt Groupe & Databricks

Rue Gilt Groupe offers online shoppers a unique retail experience through its flash sale model. The company decided to build MyRue, a Collaborative Filtering (CF) recommendation engine, on AWS with the help of Databricks. Rue Gilt Groupe is now able to provide users with a more personalized browsing experience.

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Pandora & Anodot

Pandora is one of the world’s most powerful music discovery platforms. Pandora’s anomaly-detection system had limitations in its detection models. Using Anodot’s AI-powered time series analytics solution, Pandora now monitors system operations and health in near real-time.

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Lyft & Anodot

Lyft didn’t have the resources to manually monitor every metric it gathered to detect anomalies in its data. To accurately detect anomalies at scale that could signal larger problems and require immediate attention, Lyft turned to the automation and machine learning (ML) capabilities of Anodot.

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Trifacta

Trifacta makes data wrangling a faster and more intuitive process. Trifacta considers its product to be an intelligent tool that gets better with use. The company continues to improve its product based on the user experience. Trifacta offers its Wrangler data preparation platform as software as a service (SaaS).

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Consensus & Trifacta

Consensus built a platform for retailers that simplifies the complex process of “activated selling,” or selling subscription-based products. The company uses data preparation and machine learning from Trifacta to identify retail fraud. 

Machine Learning Videos

Royal FloraHolland & Xebia

Royal FloraHolland, the world’s largest flower auction company, worked with APN Partner Xebia on a machine learning solution that includes gaining more accurate trolley predictions, leading to greater operational efficiencies, better customer outcomes, and Euros saved. 

TINE & Crayon

TINE, a Norwegian dairy cooperative owned by farmers, worked with APN Partner Crayon to gather more than 2.5 million data points from its cows to improve their health, fertility, and production. Crayon's technologies helped TINE use machine learning to increase production and contribute to the happiness of its cows.

Machine Learning Blog Posts

Artificial Intelligence and Machine Learning: Going Beyond the Hype to Drive Better Business Outcomes

By Kris Skrinak
APN Machine Learning Segment Lead at AWS

The Curse of Big Data Labeling and Three Ways to Solve It

By Jennifer Prendki
VP of Machine Learning at Figure Eight

An Executive’s Guide to Delivering Business Value Through Data-Driven Innovation and AI

By Lars Joakim Nilsson
Managing Director of Advanced Analytics and Big Data at Inmeta

Understanding the Data Science Life Cycle to Drive Competitive Advantage

By Josh Poduska
Chief Data Scientist at Domino Data Lab

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