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Build a crop segmentation machine learning model with Planet data and Amazon SageMaker geospatial capabilities

AWS Machine Learning Blog

In this post, we illustrate how to use a segmentation machine learning (ML) model to identify crop and non-crop regions in an image. Identifying crop regions is a core step towards gaining agricultural insights, and the combination of rich geospatial data and ML can lead to insights that drive decisions and actions.

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Build a contextual text and image search engine for product recommendations using Amazon Bedrock and Amazon OpenSearch Serverless

AWS Machine Learning Blog

We detail the steps to use an Amazon Titan Multimodal Embeddings model to encode images and text into embeddings, ingest embeddings into an OpenSearch Service index, and query the index using the OpenSearch Service k-nearest neighbors (k-NN) functionality. You then display the top similar results.

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Build a reverse image search engine with Amazon Titan Multimodal Embeddings in Amazon Bedrock and AWS managed services

AWS Machine Learning Blog

To upload the dataset Download the dataset : Go to the Shoe Dataset page on Kaggle.com and download the dataset file (350.79MB) that contains the images. To search against the database, you can use a vector search, which is performed using the k-nearest neighbors (k-NN) algorithm.

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Talk to your slide deck using multimodal foundation models hosted on Amazon Bedrock and Amazon SageMaker – Part 2

AWS Machine Learning Blog

We perform a k-nearest neighbor (k-NN) search to retrieve the most relevant embeddings matching the user query. This notebook will download a publicly available slide deck , convert each slide into the JPG file format, and upload these to the S3 bucket. We run these notebooks one by one. I need numbers."

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Talk to your slide deck using multimodal foundation models hosted on Amazon Bedrock and Amazon SageMaker – Part 1

AWS Machine Learning Blog

We perform a k-nearest neighbor (k=1) search to retrieve the most relevant embedding matching the user query. Setting k=1 retrieves the most relevant slide to the user question. In this notebook, we download the LLaVA-v1.5-7B As per the AI/ML flywheel, what do the AWS AI/ML services provide?

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Easily build semantic image search using Amazon Titan

AWS Machine Learning Blog

The previous post discussed how you can use Amazon machine learning (ML) services to help you find the best images to be placed along an article or TV synopsis without typing in keywords. Amazon Rekognition automatically recognizes tens of thousands of well-known personalities in images and videos using ML.

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8 of the Top Python Libraries You Should be Using in 2024

ODSC - Open Data Science

It is a library for array manipulation that has been downloaded hundreds of times per month and stands at over 25,000 stars on GitHub. PyTorch This essential library is an open-source ML framework capable of speeding up research prototyping, allowing companies to enter the production deployment phase.

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