PyImageSearch

DECEMBER 23, 2024

These scenarios demand efficient algorithms to process and retrieve relevant data swiftly. This is where Approximate Nearest Neighbor (ANN) search algorithms come into play. ANN algorithms are designed to quickly find data points close to a given query point without necessarily being the absolute closest.

K-nearest Neighbors 93

K-nearest Neighbors Algorithm Deep Learning Deep Learning 93

Data Science Dojo

FEBRUARY 14, 2024

Feature Engineering is a process of using domain knowledge to extract and transform features from raw data. These features can be used to improve the performance of Machine Learning Algorithms. Normalization A feature scaling technique is often applied as part of data preparation for machine learning.

K-nearest Neighbors 243

K-nearest Neighbors Machine Learning Machine Learning Support Vector Machines 243

Dataconomy

MARCH 4, 2025

It’s an integral part of data analytics and plays a crucial role in data science. By utilizing algorithms and statistical models, data mining transforms raw data into actionable insights. Each stage is crucial for deriving meaningful insights from data.

Data Mining 91

Data Mining Data Mining Data Mining Decision Trees 91

PyImageSearch

JANUARY 27, 2025

Random Projection The first step in the algorithm is to sample random vectors in the same -dimensional space as input vector. We will start by setting up libraries and data preparation. Setting Up Baseline with the k-NN Algorithm With our word embeddings ready, let’s implement a -Nearest Neighbors (k-NN) search. -NN

K-nearest Neighbors 76

K-nearest Neighbors Algorithm Data Preparation Database 76

Mlearning.ai

NOVEMBER 29, 2023

All the previously, recently, and currently collected data is used as input for time series forecasting where future trends, seasonal changes, irregularities, and such are elaborated based on complex math-driven algorithms. The selection of the number of neighbors and feature selection is a daunting task.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Towards AI

JULY 19, 2023

Check out the previous post to get a primer on the terms used) Outline Dealing with Class Imbalance Choosing a Machine Learning model Measures of Performance Data Preparation Stratified k-fold Cross-Validation Model Building Consolidating Results 1. among supervised models and k-nearest neighbors, DBSCAN, etc.,

Machine Learning 40

Machine Learning Machine Learning K-nearest Neighbors Support Vector Machines 40

Pickl AI

NOVEMBER 18, 2024

Key steps involve problem definition, data preparation, and algorithm selection. Data quality significantly impacts model performance. It involves algorithms that identify and use data patterns to make predictions or decisions based on new, unseen data.

Machine Learning 52

Machine Learning Machine Learning Decision Trees Algorithm 52