Artificial Intelligence
Category: *Post Types
How Medidata used Amazon SageMaker asynchronous inference to accelerate ML inference predictions up to 30 times faster
This post is co-written with Rajnish Jain, Priyanka Kulkarni and Daniel Johnson from Medidata. Medidata is leading the digital transformation of life sciences, creating hope for millions of patients. Medidata helps generate the evidence and insights to help pharmaceutical, biotech, medical devices, and diagnostics companies as well as academic researchers with accelerating value, minimizing risk, […]
Use ADFS OIDC as the IdP for an Amazon SageMaker Ground Truth private workforce
To train a machine learning (ML) model, you need a large, high-quality, labeled dataset. Amazon SageMaker Ground Truth helps you build high-quality training datasets for your ML models. With Ground Truth, you can use workers from either Amazon Mechanical Turk, a vendor company of your choosing, or an internal, private workforce to enable you to […]
How Amp on Amazon used data to increase customer engagement, Part 2: Building a personalized show recommendation platform using Amazon SageMaker
Amp is a new live radio app from Amazon. With Amp, you can host your own radio show and play songs from the Amazon Music catalog, or tune in and listen to shows other Amp users are hosting. In an environment where content is plentiful and diverse, it’s important to tailor the user experience to […]
How Amp on Amazon used data to increase customer engagement, Part 1: Building a data analytics platform
Amp, the new live radio app from Amazon, is a reinvention of radio featuring human-curated live audio shows. It’s designed to provide a seamless customer experience to listeners and creators by debuting interactive live audio shows from your favorite artists, radio DJs, podcasters, and friends. However, as a new product in a new space for […]
Build repeatable, secure, and extensible end-to-end machine learning workflows using Kubeflow on AWS
This is a guest blog post cowritten with athenahealth. athenahealth a leading provider of network-enabled software and services for medical groups and health systems nationwide. Its electronic health records, revenue cycle management, and patient engagement tools allow anytime, anywhere access, driving better financial outcomes for its customers and enabling its provider customers to deliver better quality […]
How The Chefz serves the perfect meal with Amazon Personalize
This is a guest post by Ramzi Alqrainy, Chief Technology Officer, The Chefz. The Chefz is a Saudi-based online food delivery startup, founded in 2016. At the core of The Chefz’s business model is enabling its customers to order food and sweets from top elite restaurants, bakeries, and chocolate shops. In this post, we explain […]
Create a batch recommendation pipeline using Amazon Personalize with no code
With personalized content more likely to drive customer engagement, businesses continuously seek to provide tailored content based on their customer’s profile and behavior. Recommendation systems in particular seek to predict the preference an end-user would give to an item. Some common use cases include product recommendations on online retail stores, personalizing newsletters, generating music playlist […]
Explore Amazon SageMaker Data Wrangler capabilities with sample datasets
Data preparation is the process of collecting, cleaning, and transforming raw data to make it suitable for insight extraction through machine learning (ML) and analytics. Data preparation is crucial for ML and analytics pipelines. Your model and insights will only be as reliable as the data you use for training them. Flawed data will produce […]
Conduct what-if analyses with Amazon Forecast, up to 80% faster than before
Now with Amazon Forecast, you can seamlessly conduct what-if analyses up to 80% faster to analyze and quantify the potential impact of business levers on your demand forecasts. Forecast is a service that uses machine learning (ML) to generate accurate demand forecasts, without requiring any ML experience. Simulating scenarios through what-if analyses is a powerful […]
Best practices for TensorFlow 1.x acceleration training on Amazon SageMaker
Today, a lot of customers are using TensorFlow to train deep learning models for their clickthrough rate in advertising and personalization recommendations in ecommerce. As the behavior of their clients change, they can accumulate large amounts of new data every day. Model iteration is one of a data scientist’s daily jobs, but they face the […]








