KNN in Python using Sklearn Iris Dataset | Code & Evaluation Metricsknn using sklearn
In this video, we build a K-Nearest Neighbors (KNN) Classifier using Python and the famous Iris Dataset in Google Colab.
This is not just another KNN implementation video! Along with the code, we thoroughly understand the dataset, perform data analysis and visualization, and evaluate the model using multiple performance metrics that are rarely covered in most KNN tutorials.
📌 What you'll learn in this video:
✅ Importing required Python libraries
✅ Understanding the Iris Dataset (Features & Target Classes)
✅ Exploring and analyzing the data
✅ Visualizing the dataset using plots
✅ Defining features (X) and target variable (y)
✅ Splitting data into Training and Testing sets
✅ Building the KNN Classifier using Scikit-Learn
✅ Making predictions on test data
✅ Evaluating the model using multiple metrics:
Accuracy Score
Confusion Matrix
Classification Report
Precision
Recall
F1-Score
🛠️ Tools & Libraries Used:
Python
Google Colab
NumPy
Pandas
Matplotlib
Chapters
0:30 Dataset overview
3:09 Coding exercise
14:55 Dataset visualization
18:15 Evaluate your model
25:35 Bonus!
Whether you're a beginner in Machine Learning or preparing for interviews, this end-to-end implementation will help you understand how KNN works in practice and how to properly evaluate a classification model.
Code files are provided in Google Colab for easy practice and hands-on learning.
Iris Dataset & Wine Dataset Colab Notebook:
https://discord .gg/Szam49xus
#MachineLearning #KNN #KNearestNeighbors #Python #ScikitLearn #Sklearn #IrisDataset #GoogleColab #DataScience #PythonForBeginners #MachineLearningTutorial #Classification #AI #DataAnalytics #MLProjects #LearnPython #CodingTutorial #DataVisualization #ConfusionMatrix #ClassificationReport
On this page of the site you can watch the video online KNN in Python using Sklearn Iris Dataset | Code & Evaluation Metricsknn using sklearn with a duration of hours minute second in good quality, which was uploaded by the user Enymany Tech 18 June 2026, share the link with friends and acquaintances, this video has already been watched 25 times on youtube and it was liked by 0 viewers. Enjoy your viewing!
