Flipboard

NOVEMBER 17, 2023

Generative AI models have the potential to revolutionize enterprise operations, but businesses must carefully consider how to harness their power while overcoming challenges such as safeguarding data and ensuring the quality of AI-generated content. k-NN works by finding the k most similar vectors to a given vector.

K-nearest Neighbors 169

K-nearest Neighbors AWS Clustering Database 169

Towards AI

APRIL 4, 2024

Last Updated on April 4, 2024 by Editorial Team Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. Created by the author with DALL E-3 Machine learning algorithms are the “cool kids” of the tech industry; everyone is talking about them as if they were the newest, greatest meme.

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K-nearest Neighbors Machine Learning Machine Learning Decision Trees 81

Towards AI

APRIL 7, 2024

Author(s): Stephen Chege-Tierra Insights Originally published on Towards AI. Created by the author with DALL E-3 Statistics, regression model, algorithm validation, Random Forest, K Nearest Neighbors and Naïve Bayes— what in God’s name do all these complicated concepts have to do with you as a simple GIS analyst?

Machine Learning 105

Machine Learning Machine Learning K-nearest Neighbors Supervised Learning 105

Pickl AI

JANUARY 21, 2025

k-Nearest Neighbors (k-NN) k-NN is a simple algorithm that classifies new instances based on the majority class among its k nearest neighbours in the training dataset. K-Means Clustering K-means clustering partitions data into k distinct clusters based on feature similarity.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

AWS Machine Learning Blog

NOVEMBER 13, 2024

In the context of generative AI , significant progress has been made in developing multimodal embedding models that can embed various data modalities—such as text, image, video, and audio data—into a shared vector space. He is particularly passionate about AI/ML and enjoys building proof-of-concept solutions for his customers.

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AWS Database K-nearest Neighbors AI 115

AWS Machine Learning Blog

FEBRUARY 5, 2025

OpenSearchs vector capabilities help accelerate AI application development, making it easier for teams to operationalize, manage, and integrate AI-driven assets. OpenSearch Service then uses the vectors to find the k-nearest neighbors (KNN) to the vectorized search term and image to retrieve the relevant listings.

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K-nearest Neighbors Machine Learning Machine Learning Database 82

IBM Journey to AI blog

DECEMBER 20, 2023

That’s why diversifying enterprise AI and ML usage can prove invaluable to maintaining a competitive edge. 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. What is machine learning?

Machine Learning 92

Machine Learning Machine Learning Supervised Learning Clustering 92

Dataconomy

APRIL 4, 2023

LaMDA, GPT, and more… Nowadays, everyone talking about AI models and what they are capable of. The use of AI models is expanding rapidly across all industries. AI’s capacity to find solutions to difficult issues with minimal human input is a major selling point for the technology. What is an AI model?

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K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

APRIL 4, 2023

LaMDA, GPT, and more… Nowadays, everyone talking about AI models and what they are capable of. The use of AI models is expanding rapidly across all industries. AI’s capacity to find solutions to difficult issues with minimal human input is a major selling point for the technology. What is an AI model?

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Towards AI

APRIL 14, 2023

Last Updated on April 17, 2023 by Editorial Team Author(s): Kevin Berlemont, PhD Originally published on Towards AI. The prediction is then done using a k-nearest neighbor method within the embedding space. The feature space reduction is performed by aggregating clusters of features of balanced size.

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K-nearest Neighbors Algorithm Clustering Support Vector Machines 98

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. There are different kinds of unsupervised learning algorithms, including clustering, anomaly detection, neural networks, etc. It can be either agglomerative or divisive.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Clustering 52

Towards AI

FEBRUARY 19, 2025

Last Updated on February 20, 2025 by Editorial Team Author(s): Afaque Umer Originally published on Towards AI. With AI and Large Language Models (LLMs) taking over the world (hopefully not like Skynet 🤖), we need smarter ways to store and retrieve high-dimensional data. Traditional databases? They tap out. 💡 Why?

Database 70

Database K-nearest Neighbors Machine Learning Machine Learning 70

IBM Journey to AI blog

DECEMBER 19, 2023

Common machine learning algorithms for supervised learning include: K-nearest neighbor (KNN) algorithm : This algorithm is a density-based classifier or regression modeling tool used for anomaly detection. “Means,” or average data, refers to the points in the center of the cluster that all other data is related to.

Machine Learning 82

Machine Learning Machine Learning Supervised Learning K-nearest Neighbors 82

Mlearning.ai

FEBRUARY 17, 2023

But I also want truly define that ML isn’t represent some kind of unsecured AI technologies, super brain or dark magic, it’s clear combination of programming skills, enough amount of data, cloud solutions, theory of algorithms and math  — that’s all we should have to be able to work in this branch. In this article, I will cover all of them.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Clustering 52

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. What this means is, in practice when we ran this method, we needed a cluster of machines in order to do a single pass.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

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. What this means is, in practice when we ran this method, we needed a cluster of machines in order to do a single pass.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

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. What this means is, in practice when we ran this method, we needed a cluster of machines in order to do a single pass.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Deep Learning Deep Learning 52

AWS Machine Learning Blog

APRIL 19, 2024

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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AWS ML ML Database 125

Pickl AI

AUGUST 22, 2023

This harmonization is particularly critical in algorithms such as k-Nearest Neighbors and Support Vector Machines, where distances dictate decisions. Scaling steps in as a guardian, harmonizing the scales and ensuring that algorithms treat each feature fairly.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

AWS Machine Learning Blog

APRIL 5, 2023

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. This includes configuring an OpenSearch Service cluster, ingesting item embedding, and performing free text and image search queries.

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ML ML AWS K-nearest Neighbors 111

AWS Machine Learning Blog

JANUARY 6, 2023

OpenSearch Service currently has tens of thousands of active customers with hundreds of thousands of clusters under management processing trillions of requests per month. OpenSearch Service offers the latest versions of OpenSearch, support for 19 versions of Elasticsearch (1.5 Solution overview. Prerequisites.

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AWS ML ML Machine Learning 101

Pickl AI

SEPTEMBER 3, 2023

In 2023, the expected reach of the AI market is supposed to reach the $500 billion mark and in 2030 it is supposed to reach $1,597.1 49% of companies in the world that use Machine Learning and AI in their marketing and sales processes apply it to identify the prospects of sales.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Algorithm 52

Snorkel AI

JANUARY 26, 2023

Snorkel AI co-founder and CEO Alex Ratner recently interviewed several Snorkel researchers about their published academic papers. 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.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Computer Science Computer Science 52

Snorkel AI

JANUARY 26, 2023

Snorkel AI co-founder and CEO Alex Ratner recently interviewed several Snorkel researchers about their published academic papers. 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.

K-nearest Neighbors 52

K-nearest Neighbors Clustering Computer Science Computer Science 52

Flipboard

FEBRUARY 7, 2025

DeepSeek-R1 is a powerful and cost-effective AI model that excels at complex reasoning tasks. This example provides a solution for enterprises looking to enhance their AI capabilities. To learn more about deploying DeepSeek-R1 on SageMaker, refer to Deploying DeepSeek-R1 Distill Model on AWS using Amazon SageMaker AI.

Database 82

Database AWS Python ML 82

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. Clustering and dimensionality reduction are common tasks in unSupervised Learning. Random Forests).

Machine Learning 52

Machine Learning Machine Learning Decision Trees Algorithm 52

Mlearning.ai

JULY 6, 2023

The sub-categories of this approach are negative sampling, clustering, knowledge distillation, and redundancy reduction. Some common quantitative evaluations are linear probing , K nearest neighbors (KNN), and fine-tuning. D BECOME a WRITER at MLearning.ai // invisible ML // Detect AI img Mlearning.ai

Supervised Learning 52

Supervised Learning Deep Learning Deep Learning K-nearest Neighbors 52

Mlearning.ai

MAY 21, 2023

How to perform Face Recognition using KNN So in this blog, we will see how we can perform Face Recognition using KNN (K-Nearest Neighbors Algorithm) and Haar cascades. Checkout the code walkthrough [link] 13. 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 K-nearest Neighbors Python 52

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. Clustering: An unsupervised Machine Learning technique that groups similar data points based on their inherent similarities.

Data Analyst 52

Data Analyst Data Science Machine Learning Machine Learning 52

The MLOps Blog

DECEMBER 19, 2022

A set of classes sometimes forms a group/cluster. So, we can plot the high-dimensional vector space into lower dimensions and evaluate the integrity at the cluster level. index.add(xb) # xq are query vectors, for which we need to search in xb to find the k nearest neighbors. # Creating the index.

ML 52

ML ML Algorithm Deep Learning 52

Pickl AI

DECEMBER 9, 2024

k-Nearest Neighbors (k-NN) The k-NN algorithm assumes that similar data points are close to each other in feature space. However, it can struggle with high-dimensional data, as “closeness” becomes less meaningful in such spaces (curse of dimensionality).

Machine Learning 52

Machine Learning Machine Learning Decision Trees Natural Language Processing 52

Mlearning.ai

JUNE 6, 2023

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. AI learns to play Flappy Bird Game - Python Project 37.

Machine Learning 52

Machine Learning Machine Learning Python Deep Learning 52

DagsHub

DECEMBER 23, 2024

This allows organizations to grow their AI capabilities more efficiently without needing to rebuild their entire data collection and labeling process for each new use case.  This allows it to evaluate and find relationships between the data points which is essential for clustering. 

Deep Learning 52

Deep Learning Deep Learning Supervised Learning Clustering 52

AWS Machine Learning Blog

FEBRUARY 25, 2025

AI now plays a pivotal role in the development and evolution of the automotive sector, in which Applus+ IDIADA operates. In this post, we showcase the research process undertaken to develop a classifier for human interactions in this AI-based environment using Amazon Bedrock.

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Algorithm Machine Learning Machine Learning K-nearest Neighbors 78

Flipboard

JANUARY 24, 2025

A right-sized cluster will keep this compressed index in memory. As an AI-centered platform, it creates direct pathways from customer feedback to product development, helping over 1,000 companies accelerate growth with accurate search, fast analytics, and customizable workflows. Anshu Avinash, Head of AI and Search at DevRev.

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K-nearest Neighbors ML ML Algorithm 140

Google Research AI blog

NOVEMBER 28, 2022

Sara Mahdavi , Rapha Gontijo Lopes , Tim Salimans , Jonathan Ho , David J Fleet , Mohammad Norouzi EXPO Day Workshops Graph Neural Networks in Tensorflow: A Practical Guide Workshop Organizers include: Bryan Perozzi , Sami Abu-el-Haija A Hands-On Introduction to Tensorflow and Jax Workshop Organizers include: Josh Gordon Affinity Workshops LatinX in (..)

Machine Learning 52

Machine Learning Machine Learning Algorithm Clustering 52

AWS Machine Learning Blog

NOVEMBER 1, 2024

Independent software vendors (ISVs) like Druva are integrating AI assistants into their user applications to make software more accessible. Dru , the Druva backup AI copilot, enables real-time interaction and personalized responses, with users engaging in a natural conversation with the software.

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Python AI AI K-nearest Neighbors 109