PyImageSearch

DECEMBER 23, 2024

Or think about a real-time facial recognition system that must match a face in a crowd to a database of thousands. These scenarios demand efficient algorithms to process and retrieve relevant data swiftly. This is where Approximate Nearest Neighbor (ANN) search algorithms come into play.

K-nearest Neighbors 101

K-nearest Neighbors Algorithm Deep Learning Deep Learning 101

Dataconomy

MARCH 4, 2025

Data mining is a fascinating field that blends statistical techniques, machine learning, and database systems to reveal insights hidden within vast amounts of data. Businesses across various sectors are leveraging data mining to gain a competitive edge, improve decision-making, and optimize operations.

Data Mining 91

Data Mining Data Mining Data Mining Decision Trees 91

PyImageSearch

JANUARY 27, 2025

Refinement: The candidate set is then refined by computing the actual distances between the query point and the candidates to find the approximate nearest neighbors. Developed by Moses Charikar, SimHash is particularly effective for high-dimensional data (e.g., We will start by setting up libraries and data preparation.

K-nearest Neighbors 82

K-nearest Neighbors Algorithm Data Preparation Database 82

Mlearning.ai

NOVEMBER 29, 2023

K-Nearest Neighbor Regression Neural Network (KNN) The k-nearest neighbor (k-NN) algorithm is one of the most popular non-parametric approaches used for classification, and it has been extended to regression. Decision Trees ML-based decision trees are used to classify items (products) in the database.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

AWS Machine Learning Blog

SEPTEMBER 25, 2024

Solution overview In this solution, we start with data preparation, where the raw datasets can be stored in an Amazon Simple Storage Service (Amazon S3) bucket. We provide a Jupyter notebook to preprocess the raw data and use the Amazon Titan Multimodal Embeddings model to convert the image and text into embedding vectors.

AWS 88

AWS K-nearest Neighbors ML ML 88

Pickl AI

NOVEMBER 18, 2024

Key steps involve problem definition, data preparation, and algorithm selection. Data quality significantly impacts model performance. The type of data you collect is essential, and it falls into two main categories: structured and unstructured data. This data can come from databases, APIs, or public datasets.

Machine Learning 52

Machine Learning Machine Learning Algorithm Decision Trees 52

The MLOps Blog

DECEMBER 19, 2022

However, Data Preparation, Data Sampling Strategy, selection of appropriate Distance Metrics, selection of the appropriate Loss function, and the structure of the network determine the performance of these models as well. Adding vectors to the index (xb are database vectors that are to be indexed). Creating the index.

ML 52

ML ML Algorithm Deep Learning 52