Machine Learning for Real-Time Advertising

Customers need to quickly analyze real-time advertising data to optimize cost and performance. With Machine Learning for Real-Time Advertising solutions, customers can apply machine learning (ML) to openRTB data sets to filter out unwanted inbound and outbound bid requests, forecast campaign delivery, and inform pricing tactics. ML helps customers innovate and differentiate their real-time advertising strategies.

Partner Solutions
Guidance

Partner Solutions
Guidance

Partner Solutions

Guidance

Partner Solutions

Software, SaaS, or managed services from AWS Partners

Databricks Real-Time Bidding Optimization Solution Accelerator

Databricks Lakehouse Real-Time Bidding Optimization Solution Accelerator enables customer advertising business teams extract real-time insights to make crucial business decisions for successful ad delivery and performance.

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Guidance

Prescriptive architectural diagrams, sample code, and technical content

Low-Latency High-Throughput Model Inference Using Amazon ECS

This Guidance demonstrates how to build a real-time machine learning (ML) inferencing solution on AWS that can serve millions of requests per second.
Machine Learning for Near Real-Time Advertising on AWS

This Guidance helps AdTech users build, train, and deploy machine learning models to an ad auction server application. This helps reduce unanswered bid requests by decoupling model creation and model consumption into separate environments to enable independent scale and security measures.

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