Towards AI

APRIL 4, 2024

Machine learning (ML) has proven that it is here with us for the long haul, everyone who had their doubts by calling it a phase should by now realize how wrong they are, ML has being used in various sector’s of society such as medicine, geospatial data, finance, statistics and robotics.

K-nearest Neighbors 74

K-nearest Neighbors Machine Learning Machine Learning Decision Trees 74

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 AI AI 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 AI AI 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. With GraphStorm, we release the tools that Amazon uses internally to bring large-scale graph ML solutions to production. license on GitHub. GraphStorm 0.1

ML 87

ML ML K-nearest Neighbors AWS 87

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. However, the growing influence of ML isn’t without complications.

Machine Learning 82

Machine Learning Machine Learning Supervised Learning Clustering 82

Snorkel AI

APRIL 28, 2023

Ce Zhang is an associate professor in Computer Science at ETH Zürich. The talk explored Zhang’s work on how debugging data can lead to more accurate and more fair ML applications. You can approximate your machine learning training components into some simpler classifiers—for example, a k-nearest neighbors classifier.

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. The talk explored Zhang’s work on how debugging data can lead to more accurate and more fair ML applications. You can approximate your machine learning training components into some simpler classifiers—for example, a k-nearest neighbors classifier.

ML 52

ML ML Machine Learning Machine Learning 52