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Reduce food waste to improve sustainability and financial results in retail with Amazon Forecast

AWS Machine Learning

To achieve these operational benefits, they implemented a number of best practice processes, including a fast data iteration and testing cycle, and parallel testing to find optimal data combinations. We can then call a Forecast API to create a dataset group and import data from the processed S3 bucket.

APIs 97
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Architect defense-in-depth security for generative AI applications using the OWASP Top 10 for LLMs

AWS Machine Learning

The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.

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How Amp on Amazon used data to increase customer engagement, Part 2: Building a personalized show recommendation platform using Amazon SageMaker

AWS Machine Learning

This is Part 2 of a series on using data analytics and ML for Amp and creating a personalized show recommendation list platform. The platform has shown a 3% boost to customer engagement metrics tracked (liking a show, following a creator, enabling upcoming show notifications) since its launch in May 2022.

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Identify objections in customer conversations using Amazon Comprehend to enhance customer experience without ML expertise

AWS Machine Learning

In this post, we explore how AWS customer Pro360 used the Amazon Comprehend custom classification API , which enables you to easily build custom text classification models using your business-specific labels without requiring you to learn machine learning (ML), to improve customer experience and reduce operational costs.

APIs 62
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How Amp on Amazon used data to increase customer engagement, Part 1: Building a data analytics platform

AWS Machine Learning

Amp wanted a scalable data and analytics platform to enable easy access to data and perform machine leaning (ML) experiments for live audio transcription, content moderation, feature engineering, and a personal show recommendation service, and to inspect or measure business KPIs and metrics. Solution overview.

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Identify rooftop solar panels from satellite imagery using Amazon Rekognition Custom Labels

AWS Machine Learning

To test the model output, we use a Jupyter notebook to run Python code to detect custom labels in a supplied image by calling Amazon Rekognition APIs. The solution workflow is as follows: Store satellite imagery data in Amazon S3 as the input source. Store satellite imagery data in Amazon S3 as an input source.

APIs 70
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How Patsnap used GPT-2 inference on Amazon SageMaker with low latency and cost

AWS Machine Learning

They use big data (such as a history of past search queries) to provide many powerful yet easy-to-use patent tools. In this section, we show how to build your own container, deploy your own GPT-2 model, and test with the SageMaker endpoint API. implement the model and the inference API. gpt2 and predictor.py

APIs 66