Clustering, Events and K-nearest Neighbors

Top 8 Machine Learning Algorithms

Data Science Dojo

JULY 15, 2024

K-Nearest Neighbors (KNN): This method classifies a data point based on the majority class of its K nearest neighbors in the training data. These anomalies can signal potential errors, fraud, or critical events that require attention. Points far away from others are considered anomalies.

Machine Learning

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Use language embeddings for zero-shot classification and semantic search with Amazon Bedrock

AWS Machine Learning Blog

FEBRUARY 13, 2025

Amazon Simple Queue Service (Amazon SQS) Amazon SQS is used to queue events. It consumes one event at a time so it doesnt hit the rate limit of Cohere in Amazon Bedrock. The following image uses these embeddings to visualize how topics are clustered based on similarity and meaning. What are embeddings?

AWS

AWS K-nearest Neighbors Clustering Algorithm

Build a Search Engine: Setting Up AWS OpenSearch

Flipboard

MAY 5, 2025

Amazon OpenSearch Service is a fully managed solution that simplifies the deployment, operation, and scaling of OpenSearch clusters in the AWS Cloud. Log and Event Analytics: Index, store, and analyze logs from cloud applications, security monitoring tools, and observability platforms to detect trends and troubleshoot issues.

AWS

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Webinars

What’s New in Apache Airflow® 3.0—And How Will It Reshape Your Data Workflows?

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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

FEBRUARY 5, 2025

The listing writer microservice publishes listing change events to an Amazon Simple Notification Service (Amazon SNS) topic, which an Amazon Simple Queue Service (Amazon SQS) queue subscribes to. The cluster comprises 3 cluster manager nodes (m6g.xlarge.search instance) dedicated to manage cluster operations.

K-nearest Neighbors

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Credit Card Fraud Detection Using Spectral Clustering

PyImageSearch

SEPTEMBER 16, 2024

Home Table of Contents Credit Card Fraud Detection Using Spectral Clustering Understanding Anomaly Detection: Concepts, Types and Algorithms What Is Anomaly Detection? Spectral clustering, a technique rooted in graph theory, offers a unique way to detect anomalies by transforming data into a graph and analyzing its spectral properties.

Clustering

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Implement semantic video search using open source large vision models on Amazon SageMaker and Amazon OpenSearch Serverless

Flipboard

JUNE 6, 2025

We introduce some use case-specific methods, such as temporal frame smoothing and clustering, to enhance the video search performance. Less frequent frame sampling might make sense when working with longer videos, whereas more frequent frame sampling might be needed to catch fast-occurring events.

AWS

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Anomaly detection in machine learning: Finding outliers for optimization of business functions

IBM Journey to AI blog

DECEMBER 19, 2023

As organizations collect larger data sets with potential insights into business activity, detecting anomalous data, or outliers in these data sets, is essential in discovering inefficiencies, rare events, the root cause of issues, or opportunities for operational improvements. But what is an anomaly and why is detecting it important?

Machine Learning

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Coactive AI’s CEO: quality beats quantity for data selection

Snorkel AI

APRIL 11, 2023

Cody Coleman, CEO and co-founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022. And effectively in the latent space, they form kind of tight clusters for these unseen concepts that are very well-connected components.

K-nearest Neighbors

K-nearest Neighbors Clustering Deep Learning Deep Learning

Coactive AI’s CEO: quality beats quantity for data selection

Snorkel AI

APRIL 11, 2023

Cody Coleman, CEO and co-founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022. And effectively in the latent space, they form kind of tight clusters for these unseen concepts that are very well-connected components.

K-nearest Neighbors

K-nearest Neighbors Clustering Deep Learning Deep Learning

Coactive AI’s CEO: quality beats quantity for data selection

Snorkel AI

APRIL 11, 2023

Cody Coleman, CEO and co-founder of Coactive AI gave a presentation entitled “Data Selection for Data-Centric AI: Quality over Quantity” at Snorkel AI’s Future of Data-Centric AI Event in August 2022. And effectively in the latent space, they form kind of tight clusters for these unseen concepts that are very well-connected components.

K-nearest Neighbors

K-nearest Neighbors Clustering Deep Learning Deep Learning

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

AWS Machine Learning Blog

JANUARY 6, 2023

This event frequently occurs in video streaming platforms that constantly purchase a variety of content from multiple vendors and production companies for a limited time. OpenSearch Service currently has tens of thousands of active customers with hundreds of thousands of clusters under management processing trillions of requests per month.

AWS

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Everything to know about Anomaly Detection in Machine Learning

Pickl AI

SEPTEMBER 3, 2023

Observations that deviate from the majority of the data are known as anomalies and might take the shape of occurrences, trends, or events that differ from customary or expected behaviour. Finding anomalous occurrences that might point to intriguing or potentially significant events is the aim of anomaly detection.

Machine Learning

Machine Learning Machine Learning K-nearest Neighbors Algorithm

Basic Data Science Terms Every Data Analyst Should Know

Pickl AI

SEPTEMBER 12, 2024

Clustering: An unsupervised Machine Learning technique that groups similar data points based on their inherent similarities. D Data Mining : The process of discovering patterns, insights, and knowledge from large datasets using various techniques such as classification, clustering, and association rule learning.

Data Analyst

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How Active Learning Can Improve Your Computer Vision Pipeline

DagsHub

DECEMBER 23, 2024

This allows it to evaluate and find relationships between the data points which is essential for clustering. Query Synthesis Scenario : Training a model to classify rare astronomical events using synthetic telescope data. Supports batch processing for quick processing for the images.

Deep Learning

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[Updated] 100+ Top Data Science Interview Questions

Mlearning.ai

MAY 23, 2023

There are majorly two categories of sampling techniques based on the usage of statistics, they are: Probability Sampling techniques: Clustered sampling, Simple random sampling, and Stratified sampling. The K-Nearest Neighbor Algorithm is a good example of an algorithm with low bias and high variance.

Data Science

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Google at NeurIPS 2022

Google Research AI blog

NOVEMBER 28, 2022

NeurIPS 2022 will be held as a hybrid event, in person in New Orleans, LA with some virtual attendance options, and includes invited talks, demonstrations and presentations of some of the latest in machine learning research.

Machine Learning

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Data Science Current

Top 8 Machine Learning Algorithms

Use language embeddings for zero-shot classification and semantic search with Amazon Bedrock

Webinars

Trending Sources

Build a Search Engine: Setting Up AWS OpenSearch

Webinars

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

Credit Card Fraud Detection Using Spectral Clustering

Implement semantic video search using open source large vision models on Amazon SageMaker and Amazon OpenSearch Serverless

Anomaly detection in machine learning: Finding outliers for optimization of business functions

Coactive AI’s CEO: quality beats quantity for data selection

Coactive AI’s CEO: quality beats quantity for data selection

Coactive AI’s CEO: quality beats quantity for data selection

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

Everything to know about Anomaly Detection in Machine Learning

Basic Data Science Terms Every Data Analyst Should Know

How Active Learning Can Improve Your Computer Vision Pipeline

[Updated] 100+ Top Data Science Interview Questions

Google at NeurIPS 2022

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