IBM Journey to AI blog

DECEMBER 20, 2023

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. What is machine learning?

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Machine Learning Machine Learning Supervised Learning Clustering 92

PyImageSearch

MAY 19, 2025

In this tutorial, well explore how OpenSearch performs k-NN (k-Nearest Neighbor) search on embeddings. How OpenSearch Uses Neural Search and k-NN Indexing Figure 6 illustrates the entire workflow of how OpenSearch processes a neural query and retrieves results using k-Nearest Neighbor (k-NN) search.

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K-nearest Neighbors AWS Deep Learning Deep Learning 91

Flipboard

JANUARY 19, 2025

Leveraging a comprehensive dataset of diverse fault scenarios, various machine learning algorithms—including Random Forest (RF), K-Nearest Neighbors (KNN), and Long Short-Term Memory (LSTM) networks—are evaluated.

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K-nearest Neighbors Machine Learning Machine Learning Algorithm 65

Flipboard

JANUARY 2, 2025

The proposed CAD system adopts the concept of deep transfer learning and uses a pre-trained convolutional neural network (CNN) named VGG19 to extract deep CNN features from the ultrasound images. 3 distinct experiments with the same deep CNN features but different classifier models (softmax, KNN, SVM) are performed.

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K-nearest Neighbors Cross Validation Computer Science Computer Science 73

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. Diego Martn Montoro is an AI Expert and Machine Learning Engineer at Applus+ Idiada Datalab.

Algorithm 84

Algorithm Machine Learning Machine Learning K-nearest Neighbors 84

Mlearning.ai

MAY 23, 2023

Hey guys, we will see some of the Best and Unique Machine Learning Projects for final year engineering students in today’s blog. Machine learning has become a transformative technology across various fields, revolutionizing complex problem-solving. final year Machine learning project.

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Machine Learning Machine Learning K-nearest Neighbors Python 52

AWS Machine Learning Blog

JUNE 9, 2023

a low-code enterprise graph machine learning (ML) framework to build, train, and deploy graph ML solutions on complex enterprise-scale graphs in days instead of months. To solve the problem of finding the field of study for any given paper, simply perform a k-nearest neighbor search on the embeddings.

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ML ML K-nearest Neighbors Machine Learning 105

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. Journal of machine learning research 9, no.

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ML ML Machine Learning Machine Learning 97

AWS Machine Learning Blog

NOVEMBER 9, 2023

Formally, often k-nearest neighbors (KNN) or approximate nearest neighbor (ANN) search is often used to find other snippets with similar semantics. He received his PhD in Computer Science from Purdue University in 2008. in Computer Science from University of Massachusetts Amherst in 2006.

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AWS Natural Language Processing K-nearest Neighbors Computer Science 123

PyImageSearch

JUNE 19, 2023

machine learning, statistics, probability, and algebra) are used to achieve this. machine learning, statistics, probability, and algebra) are employed to recommend our popular daily applications. This is where machine learning, statistics, and algebra come into play. These engines utilize user data (e.g.,

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K-nearest Neighbors Clustering Algorithm Deep Learning 57

Snorkel AI

APRIL 28, 2023

Ce Zhang is an associate professor in Computer Science at ETH Zürich. 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. When I talk about developing a single machine learning model, it’s getting more and more expensive.

ML 52

ML ML Machine Learning Machine Learning 52

Snorkel AI

APRIL 28, 2023

Ce Zhang is an associate professor in Computer Science at ETH Zürich. 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. When I talk about developing a single machine learning model, it’s getting more and more expensive.

ML 52

ML ML Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 12, 2024

Summary : This article equips Data Analysts with a solid foundation of key Data Science terms, from A to Z. By understanding crucial concepts like Machine Learning, Data Mining, and Predictive Modelling, analysts can communicate effectively, collaborate with cross-functional teams, and make informed decisions that drive business success.

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Data Analyst Data Science Machine Learning Machine Learning 52

Flipboard

FEBRUARY 7, 2025

Create an OpenSearch model When you work with machine learning (ML) models, in OpenSearch, you use OpenSearchs ml-commons plugin to create a model. Jon holds a Bachelor of the Arts from the University of Pennsylvania, and a Master of Science and a Ph. in Computer Science and Artificial Intelligence from Northwestern University.

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Database AWS Python ML 86

Snorkel AI

JANUARY 26, 2023

I am a PhD student in the computer science department at Stanford, advised by Chris Ré working on some broad themes of understanding data-centric AI, weak supervision and theoretical machine learning. So, we propose to do this sort of K-nearest-neighbors-type extension per source in the embedding space.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Computer Science Computer Science 52

Snorkel AI

JANUARY 26, 2023

I am a PhD student in the computer science department at Stanford, advised by Chris Ré working on some broad themes of understanding data-centric AI, weak supervision and theoretical machine learning. So, we propose to do this sort of K-nearest-neighbors-type extension per source in the embedding space.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Computer Science Computer Science 52

PyImageSearch

SEPTEMBER 16, 2024

Algorithms for Anomaly Detection We can divide anomaly detection algorithms ( Figure 5 ) into the following: statistical methods machine learning methods proximity-based methods ensemble methods Figure 5: Algorithms for detecting anomalies (source: Medium ). Supervised Learning These methods require labeled data to train the model.

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Clustering Algorithm Machine Learning Machine Learning 57

AWS Machine Learning Blog

NOVEMBER 18, 2024

Amazon OpenSearch Serverless is a serverless deployment option for Amazon OpenSearch Service, a fully managed service that makes it simple to perform interactive log analytics, real-time application monitoring, website search, and vector search with its k-nearest neighbor (kNN) plugin.

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K-nearest Neighbors AWS ML ML 114

Flipboard

MAY 5, 2025

Designed for real-time search, analysis, and visualization, AWS OpenSearch is widely used for log analytics, full-text search, structured search, geospatial queries, and machine learning-powered vector search. If you havent installed it yet, follow this step-by-step guide: Getting Started with Docker for Machine Learning.

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AWS Clustering Deep Learning Deep Learning 119

PyImageSearch

MAY 12, 2025

If you havent installed it yet, follow this step-by-step guide: Getting Started with Docker for Machine Learning. Powering Neural Search : Enables advanced similarity-based retrieval using OpenSearchs k-NN (k-Nearest Neighbors) indexing. Or requires a degree in computer science? pandas==2.0.3

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AWS K-nearest Neighbors Deep Learning Deep Learning 74