PyImageSearch

JUNE 19, 2023

This technique expresses a text item as a feature vector, which can be used to compute cosine similarity with other item feature vectors. Figure 7: TF-IDF calculation (source: Towards Data Science ). The item ratings of these -closest neighbors are then used to recommend items to the given user. That’s not the case.

K-nearest Neighbors 55

K-nearest Neighbors Clustering Algorithm Deep Learning 55

AWS Machine Learning Blog

JUNE 9, 2023

To solve the problem of finding the field of study for any given paper, simply perform a k-nearest neighbor search on the embeddings. Da got his PhD in computer science from the Johns Hopkins University. In this case, the model reaches an MRR of 0.31 on the test set of the constructed graph.

ML 104

ML ML K-nearest Neighbors Machine Learning 104

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. He has a degree in Mathematics and Computer Science from the University of Illinois at Urbana Champaign. Some plays are mixed into other coverage types, as shown in the following figure (right).

ML 93

ML ML Machine Learning Machine Learning 93

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. Jon holds a Bachelor of the Arts from the University of Pennsylvania, and a Master of Science and a Ph.

Database 83

Database AWS Python ML 83

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

Mlearning.ai

MAY 23, 2023

Read the full article here —  [link] For final-year students pursuing a degree in computer science or related disciplines, engaging in machine learning projects can be an excellent way to consolidate theoretical knowledge, gain practical experience, and showcase their skills to potential employers.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Python 52

Snorkel AI

APRIL 28, 2023

Ce Zhang is an associate professor in Computer Science at ETH Zürich. You can approximate your machine learning training components into some simpler classifiers—for example, a k-nearest neighbors classifier. This talk was followed by an audience Q&A conducted by Snorkel AI’s Priyal Aggarwal.

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. You can approximate your machine learning training components into some simpler classifiers—for example, a k-nearest neighbors classifier. This talk was followed by an audience Q&A conducted by Snorkel AI’s Priyal Aggarwal.

ML 52

ML ML Machine Learning Machine Learning 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. 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

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. Or requires a degree in computer science?

Clustering 55

Clustering Algorithm Machine Learning Machine Learning 55

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.

Algorithm 79

Algorithm Machine Learning Machine Learning K-nearest Neighbors 79

Flipboard

JANUARY 24, 2025

Dylan holds a BSc and MEng degree in Computer Science from Cornell University. Dylan has decades of experience working directly with customers and creating products and solutions in the database, analytics and AI/ML domain. His primary interests include distributed systems.

K-nearest Neighbors 142

K-nearest Neighbors ML ML Algorithm 142

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.

K-nearest Neighbors 113

K-nearest Neighbors AWS ML ML 113