Towards AI

APRIL 4, 2024

According to IBM, machine learning is a subfield of computer science and artificial intelligence (AI) that focuses on using data and algorithms to simulate human learning processes while progressively increasing their accuracy.

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K-nearest Neighbors Machine Learning Machine Learning Decision Trees 81

Flipboard

NOVEMBER 17, 2023

This type of data is often used in ML and artificial intelligence applications. MongoDB Atlas Vector Search uses a technique called k-nearest neighbors (k-NN) to search for similar vectors. k-NN works by finding the k most similar vectors to a given vector.

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K-nearest Neighbors AWS Clustering Database 170

ODSC - Open Data Science

DECEMBER 14, 2023

Photo Mosaics with Nearest Neighbors: Machine Learning for Digital Art In this post, we focus on a color-matching strategy that is of particular interest to a data science or machine learning audience because it utilizes a K-nearest neighbors (KNN) modeling approach.

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Towards AI

FEBRUARY 7, 2024

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. k (optional): An integer representing the number of nearest neighbors to retrieve. huggingface.co Perfect, now we have a dataset.

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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. An ensemble methodology, RF-LSTM Tuned KNN, is proposed to enhance detection accuracy and robustness.

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ODSC - Open Data Science

FEBRUARY 10, 2025

K-nearest neighbors are sufficient for detecting specific medialike in copyright protectionbut less reliable when analyzing a broad range of factors. The best type of model depends on what you want your A/V analysis to accomplish. Keep your input types, goals, computing hardware availability and budget in mind when choosing.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Natural Language Processing 52

Dataconomy

APRIL 4, 2023

Artificial intelligence (AI) is a broad term that encompasses the ability of computers and machines to perform tasks that normally require human intelligence, such as reasoning, learning, decision-making, and problem-solving. An AI model is a crucial part of artificial intelligence. What is an AI model?

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K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

APRIL 4, 2023

Artificial intelligence (AI) is a broad term that encompasses the ability of computers and machines to perform tasks that normally require human intelligence, such as reasoning, learning, decision-making, and problem-solving. An AI model is a crucial part of artificial intelligence. What is an AI model?

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K-nearest Neighbors Decision Trees AI AI 91

AWS Machine Learning Blog

FEBRUARY 13, 2025

This is the k-nearest neighbor (k-NN) algorithm. In k-NN, you can make assumptions around a data point based on its proximity to other data points. You can use the embedding of an article and check the similarity of the article against the preceding embeddings.

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AWS K-nearest Neighbors Clustering Algorithm 101

AWS Machine Learning Blog

NOVEMBER 15, 2024

The embedded image is stored in an OpenSearch index with a k-nearest neighbors (k-NN) vector field. Example with a multimodal embedding model The following is a code sample performing ingestion with Amazon Titan Multimodal Embeddings as described earlier.

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Database SQL Data Analysis Data Analysis 117

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 K-nearest Neighbors AI AI 121

IBM Journey to AI blog

DECEMBER 20, 2023

ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. Classification algorithms include logistic regression, k-nearest neighbors and support vector machines (SVMs), among others.

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

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.

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K-nearest Neighbors AWS Machine Learning Machine Learning 126

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.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Clustering 52

IBM Journey to AI blog

DECEMBER 19, 2023

In this blog we’ll go over how machine learning techniques, powered by artificial intelligence, are leveraged to detect anomalous behavior through three different anomaly detection methods: supervised anomaly detection, unsupervised anomaly detection and semi-supervised anomaly detection.

Machine Learning 82

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 82

ODSC - Open Data Science

FEBRUARY 3, 2023

Learning objectives include: Develop good features (recency, frequency, and monetary value as well as categorical transformations) for detecting and preventing fraud Identify anomalies using statistical techniques like z-scores, robust z-scores, Mahalanobis distances, k-nearest neighbors (k-NN), and local outlier factor (LOF) Identify anomalies using (..)

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K-nearest Neighbors Data Science AI AI 52

Towards AI

FEBRUARY 19, 2025

But heres the catch scanning millions of vectors one by one (a brute-force k-Nearest Neighbors or KNN search) is painfully slow. Instead, vector databases rely on Approximate Nearest Neighbors (ANN) techniques, which trade a tiny bit of accuracy for massive speed improvements.

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Database K-nearest Neighbors Machine Learning Machine Learning 70

PyImageSearch

JUNE 19, 2023

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., The item ratings of these -closest neighbors are then used to recommend items to the given user. And that’s exactly what I do.

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K-nearest Neighbors Clustering Algorithm Deep Learning 56

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.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Clustering 52

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. The user input is converted into embeddings using the Amazon Titan Text Embeddings model accessed using Amazon Bedrock. An OpenSearch Service vector search is performed using these embeddings.

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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. To make this work, we need to transform the textual interactions into a format that allows algebraic operations.

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Algorithm Machine Learning Machine Learning K-nearest Neighbors 72

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. Semantic retrieval BM25 focuses on lexical matching.

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AWS Natural Language Processing K-nearest Neighbors Computer Science 107

ODSC - Open Data Science

JANUARY 5, 2024

Scikit-learn is also open-source, which makes it a popular choice for both academic and commercial use.

Python 52

Python K-nearest Neighbors Data Science Data Visualization 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. Our field organization includes customer-facing teams (account managers, solutions architects, specialists) and internal support functions (sales operations).

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AWS Machine Learning Blog

SEPTEMBER 29, 2023

In this analysis, we use a K-nearest neighbors (KNN) model to conduct crop segmentation, and we compare these results with ground truth imagery on an agricultural region.

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Machine Learning Machine Learning ML ML 134

Flipboard

FEBRUARY 7, 2025

In most cases, you will use an OpenSearch Service vector database as a knowledge base, performing a k-nearest neighbor (k-NN) search to incorporate semantic information in the retrieval with vector embeddings. in Computer Science and Artificial Intelligence from Northwestern University.

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Database AWS Python ML 86

Mlearning.ai

APRIL 6, 2023

In contrast, for datasets with low dimensionality, simpler algorithms such as Naive Bayes or K-Nearest Neighbors may be sufficient. For datasets with high dimensionality , algorithms such as SVM or Random Forest s that can handle a large number of features may be a better choice.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

AWS Machine Learning Blog

FEBRUARY 10, 2023

We design a K-Nearest Neighbors (KNN) classifier to automatically identify these plays and send them for expert review. She works with strategic AWS customers to explore and apply artificial intelligence and machine learning to discover new insights and solve complex problems. She received her Ph.D.

ML 82

ML ML Machine Learning Machine Learning 82

Pickl AI

SEPTEMBER 12, 2024

Artificial Intelligence (AI): A branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence. K K-Means Clustering: An unsupervised learning algorithm that partitions data into K distinct clusters based on feature similarity.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 18, 2024

Basics of Machine Learning Machine Learning is a subset of Artificial Intelligence (AI) that allows systems to learn from data, improve from experience, and make predictions or decisions without being explicitly programmed. K-Nearest Neighbors), while others can handle large datasets efficiently (e.g.,

Machine Learning 52

Machine Learning Machine Learning Decision Trees Algorithm 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].

Cross Validation 52

Cross Validation Decision Trees Algorithm Natural Language Processing 52

PyImageSearch

SEPTEMBER 16, 2024

For example, The K-Nearest Neighbors algorithm can identify unusual login attempts based on the distance to typical login patterns. The Local Outlier Factor (LOF) algorithm measures the local density deviation of a data point with respect to its neighbors. And that’s exactly what I do.

Clustering 56

Clustering Algorithm Machine Learning Machine Learning 56

Mlearning.ai

JUNE 6, 2023

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. Haar cascades are very fast as compared to other ways of detecting faces (like MTCNN) but with an accuracy tradeoff.

Machine Learning 52

Machine Learning Machine Learning Python Deep Learning 52

Mlearning.ai

MAY 23, 2023

The K-Nearest Neighbor Algorithm is a good example of an algorithm with low bias and high variance. This trade-off can easily be reversed by increasing the k value which in turn results in increasing the number of neighbours. Let us see some examples. Programming: This is an obvious yet the most important skill.

Data Science 52

Data Science Decision Trees Machine Learning Machine Learning 52

Dataconomy

MARCH 28, 2025

Their application spans a wide array of tasks, from categorizing information to predicting future trends, making them an essential component of modern artificial intelligence. K-nearest neighbors (KNN): Classifies based on proximity to other data points. What are machine learning algorithms?

Machine Learning 91

Machine Learning Machine Learning Algorithm K-nearest Neighbors 91

Dataconomy

FEBRUARY 26, 2025

Causal AI refers to a specialized field of artificial intelligence that focuses on identifying cause-and-effect relationships within data. By leveraging its capabilities, businesses can optimize their strategies, improve outcomes, and even predict the effects of potential interventions in a wide range of fields. What is causal AI?

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K-nearest Neighbors AI AI Artificial Intelligence 91

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. The metadata of the response from the OpenSearch index contains a path to the image corresponding to the most relevant slide.

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