K-Nearest Neighbors Courses and Certifications

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

IEEE

On the Robustness of Deep K-Nearest Neighbors

Explore the robustness of Deep k-Nearest Neighbors against adversarial attacks, proposing a heuristic method to find vulnerabilities in this defense mechanism for deep learning models.

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

NPTEL;  IIT Kharagpur

Data Mining

42 ratings

Comprehensive exploration of data mining techniques, covering preprocessing, association rules, classification methods, and clustering algorithms for extracting valuable insights from datasets.

• YouTube
• 16 hours
• Self-Paced
• Free Video

EDUCBA

Apply R Techniques for Telecom Customer Churn Prediction

Master telecom churn prediction in R through hands-on data preparation, feature engineering, and dataset structuring for machine learning workflows.

• Coursera
• 4 hours 27 minutes
• Self-Paced
• Paid Course

Pascal Poupart

CS480-680 - K-Nearest Neighbours

Learn about k-nearest neighbours algorithm for classification and regression, including examples, machine learning concepts, and accuracy considerations.

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

Implement and assess K-Nearest Neighbors algorithm for classification. Learn data preparation, distance formulas, and model evaluation using various datasets.

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

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

Python Machine Learning Bootcamp

106 ratings at Noble Desktop

Master machine learning fundamentals through hands-on Python programming, covering regression analysis, classification algorithms, and essential data science techniques for real-world problem-solving.

• Noble Desktop
• 30 hours
• Self-Paced
• $1,895.00

Supervised Learning in R: Classification

27 ratings at DataCamp

In this course you will learn the basics of machine learning for classification.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Supervised Machine Learning in Python

Master the most popular supervised machine learning techniques to begin making predictions with labeled data.

• DataCamp
• 1 day 1 hour
• Self-Paced
• Free Trial Available

Brandon Rohrer

How K-Nearest Neighbors Works

Explore k-nearest neighbors algorithm for classification and regression, including key considerations like k value, feature scaling, and distance metrics.

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

5 Minutes Engineering

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

Explore K-Nearest Neighbors algorithm for machine learning and neural networks, covering its principles, implementation, and applications in classification and regression tasks.

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

Implementing AI Algorithms from Scratch

67 ratings at CodeSignal

Master the fundamentals of AI by implementing algorithms from scratch - from regression and gradient descent to neural networks, covering classification, ensemble methods, and unsupervised learning techniques.

• CodeSignal
• Self-Paced
• Free Certificate
• 6 courses

Classification Algorithms and Metrics

Master classification algorithms by building Logistic Regression, k-NN, Naive Bayes, and Decision Trees from scratch. Implement metrics like AUCROC and confusion matrix while gaining hands-on experience with real-world applications.

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