K-Nearest Neighbors Courses and Certifications

Classify unknown data points by their nearest neighbors: distance formulas, normalization, train/validation/test splits, and a cancer classifier project.

• Codecademy
• 3 hours
• Self-Paced
• Free Trial Available

NPTEL-NOC IITM

K-Nearest Neighbors Implementation in R

Implement K-Nearest Neighbors algorithm in R programming language. Learn practical application of this machine learning technique for classification and regression tasks.

• YouTube
• 29 minutes
• Self-Paced
• Free Video

NPTEL-NOC IITM

K-Nearest Neighbors (KNN) Algorithm - Introduction and Applications

Explore k-Nearest Neighbors algorithm: concepts, applications, assumptions, implementation, and optimization techniques for effective machine learning.

• YouTube
• 26 minutes
• Self-Paced
• Free Video

Machine Learning: Regression

20 ratings

Build regression models to predict house prices in Python: fit simple and multiple linear regression, ridge and lasso, nearest neighbor and kernel regression.

• Coursera
• 8 weeks, 3 hours a week
• Self-Paced
• Paid Course

Brandon Rohrer

How K-Nearest Neighbors Works

Explore how k-nearest neighbors handles classification and regression, including the effects of k, feature scaling, distance metrics, categorical data, and computational cost.

• YouTube
• 26 minutes
• Self-Paced
• Free Video

5 Minutes Engineering

Machine Learning and Neural Networks: K-Nearest Neighbors - Day 9

Introduces K-nearest neighbors (KNN) within a machine learning and neural network foundations series.

• YouTube
• 34 minutes
• Self-Paced
• Free Video

Aladdin Persson

K-Nearest Neighbor From Scratch - Machine Learning Python

Implement a K-nearest neighbors classifier from scratch in Python, including both an intuitive version and an efficient no-loop implementation.

• YouTube
• 25 minutes
• Self-Paced
• Free Video

Pascal Poupart

CS480-680 - K-Nearest Neighbours

Explore K-nearest neighbours for classification and regression, including accuracy, consistent hypotheses, and underfitting.

• YouTube
• 1 hour 29 minutes
• Self-Paced
• Free Video

NPTEL-NOC IITM

k-Nearest Neighbour (k-NN) Regression

Explore k-Nearest Neighbour (k-NN) Regression, comparing parametric and non-parametric models while examining the algorithm's assumptions, advantages, and limitations.

• YouTube
• 12 minutes
• Self-Paced
• Free Video

Machine Learning: Clustering & Retrieval

5 ratings

Build a document retrieval system with k-nearest neighbors, KD-trees and locality sensitive hashing, then cluster Wikipedia articles using k-means, Gaussian mixtures with EM, and LDA.

• Coursera
• 6 weeks, 3 hours a week
• Self-Paced
• Paid Course

Classification Algorithms and Metrics

Implement classification algorithms and evaluation metrics from scratch in C++, including k-NN, Naive Bayes, decision trees, Logistic Regression, and ROC AUC.

• CodeSignal
• 5 hours
• Self-Paced
• Free Certificate

Python Machine Learning Bootcamp (Live Online)

686 ratings at CourseHorse

Build the practical abilities needed to tackle real-world problems through machine learning.

• CourseHorse
• Self-Paced
• $1,895.00

Data Visualization and Modeling in Python

Visualize and model data in Python: build matplotlib line, bar, scatter, histogram and heatmap plots, code KNN from scratch, and fit linear regressions.

• Coursera
• 4 weeks, 8 hours a week
• Self-Paced
• Paid Course

Supervised Machine Learning: Classification

469 ratings at Coursera

Train classification models — logistic regression, k-nearest neighbors, support vector machines, decision trees and tree ensembles — and handle unbalanced classes with oversampling and undersampling.

• Coursera
• 6 weeks, 4 hours a week
• Self-Paced
• Paid Course

Classification Analysis

Build and compare classifiers — KNN, decision trees, SVM, naive Bayes, and logistic regression — and evaluate them with accuracy, precision, recall, F1, and ROC curves.

• Coursera
• 6 weeks, 6 hours a week
• Self-Paced
• Paid Course