AI Examples from the World's Biggest Retail Companies

432-r909-ai-for-product-research-design-and-development-1.jpg

At Manceps, we’re on a mission to help companies build and deploy AI solutions at scale. One of the things are clients ask us all the time is—

WHAT CAN YOU ACTUALLY DO WITH AI?

Going company by company, we were surprised and delighted by all the ways that Artificial Intelligence and Machine Learning are helping retail organizations make BIG CHANGES.

We’re talking super-charging operational efficiency, reducing shrink and finding ways to provide better customers service.

This deeply-sourced ebook covers more than a dozen companies and use cases.

We hope you enjoy taking a peek into the future of retail!

Featured Companies

and others!

OUR LATEST RESOURCES

OUR LATEST ARTICLES

DevFest West Coast 2020

Watch videos of some of the world's top AI experts discuss everything from Tensorflow Extended to Kubernetes to AutoML to Coral.

Video: Machine Learning Engineering with Tensorflow Extended

In this talk, Hannes is providing insights into Machine Learning Engineering with TensorFlow Extended (TFX). He introduces how TFX for machine learning pipeline tasks and how to orchestrate entire ML pipelines with TFX. The audience learns how to run ML production pipelines with Kubeflow Pipelines, and therefore, free the data scientist's time from maintaining production machine learning models.

Video: How to Build a Reproducible ML Pipeline

Solving a data science problem usually requires multiple steps. These steps can include extracting and transforming data, training a model, and deploying the model into production. In this session, we'll discuss how to specify those steps with Python into an ML pipeline. We'll show how to create a Kubeflow Pipeline, a component of the Kubeflow open-source project. The audience will learn about how to integrate TensorFlow Extended components into the pipeline, and how to deploy the pipeline to the hosted Cloud AI Pipelines environment on Google Cloud. The key takeaway is how to improve reuse and reproducibility of the machine learning process.

OUR HEADQUARTERS

Headquartered in the heart of Portland, Oregon, our satellite offices span North America, Europe, the Middle East, and Africa.

(503) 922-1164

Our address is
US Custom House
220 NW 8th Ave