AWS Machine Learning Blog

APRIL 3, 2024

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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K-nearest Neighbors AWS Machine Learning Machine Learning 119

AWS Machine Learning Blog

SEPTEMBER 6, 2023

A k-Nearest Neighbor (k-NN) index is enabled to allow searching of embeddings from the OpenSearch Service. As an Information Technology Leader, Jay specializes in artificial intelligence, data integration, business intelligence, and user interface domains.

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AWS Machine Learning Blog

APRIL 19, 2024

We perform a k-nearest neighbor (k-NN) search to retrieve the most relevant embeddings matching the user query. As per the AI/ML flywheel, what do the AWS AI/ML services provide? Based on the summary, the AWS AI/ML services provide a range of capabilities that fuel an AI/ML flywheel.

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Mlearning.ai

FEBRUARY 17, 2023

Basically, Machine learning is a part of the Artificial intelligence field, which is mainly defined as a technic that gives the possibility to predict the future based on a massive amount of past known or unknown data. ML algorithms can be broadly divided into supervised learning , unsupervised learning , and reinforcement learning.

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AWS Machine Learning Blog

SEPTEMBER 29, 2023

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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Flipboard

FEBRUARY 7, 2025

For more information, see Creating connectors for third-party ML platforms. Create an OpenSearch model When you work with machine learning (ML) models, in OpenSearch, you use OpenSearchs ml-commons plugin to create a model. You created an OpenSearch ML model group and model that you can use to create ingest and search pipelines.

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AWS Machine Learning Blog

FEBRUARY 25, 2025

Instead of treating each input as entirely unique, we can use a distance-based approach like k-nearest neighbors (k-NN) to assign a class based on the most similar examples surrounding the input. For the classfier, we employed a classic ML algorithm, k-NN, using the scikit-learn Python module.

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Pickl AI

JULY 17, 2023

Machine Learning is a subset of artificial intelligence (AI) that focuses on developing models and algorithms that train the machine to think and work like a human. It aims to partition a given dataset into K clusters, where each data point belongs to the cluster with the nearest mean.

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Machine Learning Machine Learning K-nearest Neighbors Clustering 52

AWS Machine Learning Blog

AUGUST 26, 2024

At AWS, we are transforming our seller and customer journeys by using generative artificial intelligence (AI) across the sales lifecycle. This includes sales collateral, customer engagements, external web data, machine learning (ML) insights, and more.

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AWS Machine Learning Blog

FEBRUARY 10, 2023

Through a collaboration between the Next Gen Stats team and the Amazon ML Solutions Lab , we have developed the machine learning (ML)-powered stat of coverage classification that accurately identifies the defense coverage scheme based on the player tracking data. In this post, we deep dive into the technical details of this ML model.

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ML ML Machine Learning Machine Learning 76

Mlearning.ai

APRIL 6, 2023

⚠ You can solve the below-mentioned questions from this blog ⚠ ✔ What if I am building Low code — No code ML automation tool and I do not have any orchestrator or memory management system ? ✔ how to reduce the complexity and computational expensiveness of ML models ? will my data help in this ?

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ODSC - Open Data Science

JANUARY 5, 2024

PyTorch This essential library is an open-source ML framework capable of speeding up research prototyping, allowing companies to enter the production deployment phase. Scikit-learn is also open-source, which makes it a popular choice for both academic and commercial use. Currently, Django is still at over 74,000 stars on GitHub.

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Python K-nearest Neighbors Data Science Data Visualization 52

Mlearning.ai

FEBRUARY 15, 2023

K-Nearest Neighbou r: The k-Nearest Neighbor algorithm has a simple concept behind it. The method seeks the k nearest neighbours among the training documents to classify a new document and uses the categories of the k nearest neighbours to weight the category candidates [3].

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Mlearning.ai

JUNE 6, 2023

It can also be thought of as the ‘Hello World of ML world. How to perform Face Recognition using KNN In this blog, we will see how we can perform Face Recognition using KNN (K-Nearest Neighbors Algorithm) and Haar cascades. So, In this blog, we will see how to implement it.

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Mlearning.ai

MAY 23, 2023

Let us first understand the meaning of bias and variance in detail: Bias: It is a kind of error in a machine learning model when an ML Algorithm is oversimplified. It is introduced into an ML Model when an ML algorithm is made highly complex. In such types of questions, we first need to ask what ML model we have to train.

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Data Science Decision Trees Machine Learning Machine Learning 52

Flipboard

DECEMBER 18, 2024

It supports advanced features such as result highlighting, flexible pagination, and k-nearest neighbor (k-NN) search for vector and semantic search use cases. Teams can use OpenSearch Service ML connectors which facilitate access to models hosted on third-party ML platforms. How to integrate Cohere Rerank 3.5

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Towards AI

FEBRUARY 7, 2024

Youtube Recommender – a Hugging Face Space by Ransaka Discover amazing ML apps made by the community huggingface.co Ransaka/youtube_recommendation_data · Datasets at Hugging Face We're on a journey to advance and democratize artificial intelligence through open source and open science. huggingface.co

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AWS Machine Learning Blog

DECEMBER 10, 2024

We performed a k-nearest neighbor (k-NN) search to retrieve the most relevant embedding matching the question. Proceedings of the AAAI Conference on Artificial Intelligence. Archana is an aspiring member of the AI/ML technical field community at AWS. 13636-13645. 10.1609/aaai.v37i11.26598.

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AWS Machine Learning Blog

OCTOBER 24, 2024

Evaluating a RAG solution Contrary to traditional machine learning (ML) models, for which evaluation metrics are well defined and straightforward to compute, evaluating a RAG framework is still an open problem. Practically, this can be achieved in OpenSearch by combining a k-nearest neighbors (k-NN) query with keyword matching.

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