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Unlocking the Power of KNN Algorithm in Machine Learning

Pickl AI

Nevertheless, its applications across classification, regression, and anomaly detection tasks highlight its importance in modern data analytics methodologies. The K Nearest Neighbors (KNN) algorithm of machine learning stands out for its simplicity and effectiveness. What are K Nearest Neighbors in Machine Learning?

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Five machine learning types to know

IBM Journey to AI blog

Machine learning (ML) technologies can drive decision-making in virtually all industries, from healthcare to human resources to finance and in myriad use cases, like computer vision , large language models (LLMs), speech recognition, self-driving cars and more. However, the growing influence of ML isn’t without complications.

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

AWS Machine Learning Blog

This guest post is co-written by Lydia Lihui Zhang, Business Development Specialist, and Mansi Shah, Software Engineer/Data Scientist, at Planet Labs. In this post, we illustrate how to use a segmentation machine learning (ML) model to identify crop and non-crop regions in an image.

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OfferUp improved local results by 54% and relevance recall by 27% with multimodal search on Amazon Bedrock and Amazon OpenSearch Service

AWS Machine Learning Blog

To further boost these capabilities, OpenSearch offers advanced features, such as: Connector for Amazon Bedrock You can seamlessly integrate Amazon Bedrock machine learning (ML) models with OpenSearch through built-in connectors for services, enabling direct access to advanced ML features.

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Power recommendations and search using an IMDb knowledge graph – Part 3

AWS Machine Learning Blog

We downloaded the data from AWS Data Exchange and processed it in AWS Glue to generate KG files. In Part 2 , we demonstrated how to use Amazon Neptune ML (in Amazon SageMaker ) to train the KG and create KG embeddings. Matthew Rhodes is a Data Scientist I working in the Amazon ML Solutions Lab.

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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. In her free time, she likes to go for long runs along the beach.

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Debugging data to build better and more fair ML applications

Snorkel AI

He presented “Building Machine Learning Systems for the Era of Data-Centric AI” at Snorkel AI’s The Future of Data-Centric AI event in 2022. The talk explored Zhang’s work on how debugging data can lead to more accurate and more fair ML applications. A transcript of the talk follows.

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