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Credit Card Fraud Detection Using Spectral Clustering

PyImageSearch

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.

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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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Fundamentals of Recommendation Systems

PyImageSearch

K-Nearest Neighbor K-nearest neighbor (KNN) ( Figure 8 ) is an algorithm that can be used to find the closest points for a data point based on a distance measure (e.g., Figure 8: K-nearest neighbor algorithm (source: Towards Data Science ). Several clustering algorithms (e.g.,

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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

This solution includes the following components: Amazon Titan Text Embeddings is a text embeddings model that converts natural language text, including single words, phrases, or even large documents, into numerical representations that can be used to power use cases such as search, personalization, and clustering based on semantic similarity.

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Implement unified text and image search with a CLIP model using Amazon SageMaker and Amazon OpenSearch Service

AWS Machine Learning Blog

The first step is to download the pre-trained model weighting file, put it into a model.tar.gz out" embeddings.append(json.load(open(embedding_file))[0]) Create an ML-powered unified search engine This section discusses how to create a search engine that that uses k-NN search with embeddings. file, and upload it to an S3 bucket.

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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. OpenSearch Service currently has tens of thousands of active customers with hundreds of thousands of clusters under management processing trillions of requests per month. Solution overview. Prerequisites.

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70+ Best and Unique Python Machine Learning Projects with source code [2023]

Mlearning.ai

Most dominant colors in an image using KMeans clustering In this blog, we will find the most dominant colors in an image using the K-Means clustering algorithm, this is a very interesting project and personally one of my favorites because of its simplicity and power.