Dataconomy

APRIL 4, 2023

Some of the common types are: Linear Regression Deep Neural Networks Logistic Regression Decision Trees AI Linear Discriminant Analysis Naive Bayes Support Vector Machines Learning Vector Quantization K-nearest Neighbors Random Forest What do they mean? Let’s dig deeper and learn more about them!

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Dataconomy

APRIL 4, 2023

Some of the common types are: Linear Regression Deep Neural Networks Logistic Regression Decision Trees AI Linear Discriminant Analysis Naive Bayes Support Vector Machines Learning Vector Quantization K-nearest Neighbors Random Forest What do they mean? Let’s dig deeper and learn more about them!

K-nearest Neighbors 91

K-nearest Neighbors Decision Trees AI AI 91

Pickl AI

JULY 17, 2023

It aims to partition a given dataset into K clusters, where each data point belongs to the cluster with the nearest mean. K-NN (k nearest neighbors): K-Nearest Neighbors (K-NN) is a simple yet powerful algorithm used for both classification and regression tasks in Machine Learning.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Clustering 52

AWS Machine Learning Blog

JANUARY 6, 2023

We downloaded the data from AWS Data Exchange and processed it in AWS Glue to generate KG files. In Part 2 , we demonstrated how to use Amazon Neptune ML (in Amazon SageMaker ) to train the KG and create KG embeddings. Matthew Rhodes is a Data Scientist I working in the Amazon ML Solutions Lab. About the Authors.

AWS 84

AWS ML ML Machine Learning 84

AWS Machine Learning Blog

DECEMBER 6, 2023

Another driver behind RAG’s popularity is its ease of implementation and the existence of mature vector search solutions, such as those offered by Amazon Kendra (see Amazon Kendra launches Retrieval API ) and Amazon OpenSearch Service (see k-Nearest Neighbor (k-NN) search in Amazon OpenSearch Service ), among others.

SQL 104

SQL AWS Database Analytics 104

Mlearning.ai

FEBRUARY 15, 2023

Introduction In natural language processing, text categorization tasks are common (NLP). K-Nearest Neighbou r: The k-Nearest Neighbor algorithm has a simple concept behind it. The accuracy of the ML model indicates how many times it was correct overall. Uysal and Gunal, 2014).

Cross Validation 52

Cross Validation Decision Trees Natural Language Processing Algorithm 52

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. In this post, we deep dive into the technical details of this ML model.

ML 66

ML ML Machine Learning Machine Learning 66

Mlearning.ai

JUNE 6, 2023

It can also be thought of as the ‘Hello World of ML world. 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. Natural Language Processing Projects with source code in Python 69.

Machine Learning 52

Machine Learning Machine Learning Python Deep Learning 52

Google Research AI blog

NOVEMBER 28, 2022

Organizing Committee General Chairs includes: Sanmi Koyejo Program Chairs include: Alekh Agarwal Workshop Chairs include: Hanie Sedghi Tutorial Chairs include: Adji Bousso Dieng , Jessica Schrouff Affinity Workshop Chair: Adji Bousso Dieng , Jessica Schrouff Program Committee, Senior Area Chairs include: Corinna Cortes , Claudio Gentile , Mohammad (..)

Machine Learning 52

Machine Learning Machine Learning Clustering Algorithm 52