📘 This repository offers a complete K-Nearest Neighbors (KNN) tutorial, guiding you from core theory to hands-on practice. Learn to implement KNN from scratch with NumPy, apply it using scikit-learn, and explore visualizations, datasets, and Jupyter notebooks to fully understand, test, and optimize the algorithm.

Proyek pertama predictive analytics untuk membangun model machine learning yang dapat memprediksi harga sewa rumah dan apartement di India.

The dataset provides information on crop production in India from 1997 to 2015. The Crop Production was predicted using Decision Tree Regressor, K Neighbours Regressor, Bagging Regressor, Random Forest Regressor and Gradient Boosting Regressor

🔥 Concrete Compressive Strength Predictor - using KNNR & PR Algorithms.

Implemented various Machine Learning algorithms from scratch (k-means Clustering , k-nn classifier, k-nn regressor)

🏡House Price Prediction, Artificial Intelligence course, University of Tehran

No description provided.

The objective of this repository is to share the scripts and the datasets used to train ML models presented in the paper