An implementation of the K-Nearest Neighbors algorithm from scratch using the Python programming language.

A recommender system to recommend movies, books or shopping items list based on search.

In this program, I used the KNN model to estimate Iranian universities' entrance exam (konkur) rank, and I also developed a telegram bot so users could use it.

Unsupervised anomaly detection in vibration signal using PyCaret vs BiLSTM

The task is to build a machine learning regression model will predict the number of absent hours. As Employee absenteeism is a major problem faced by every employer which eventually lead to the backlogs, piling of the work, delay in deploying the project and can have a major effect on company finances. The aim of this project is to find an issue…

Problems Identification: This project involves the implementation of efficient and effective KNN classifiers on MNIST data set. The MNIST data comprises of digital images of several digits ranging from 0 to 9. Each image is 28 x 28 pixels. Thus, the data set has 10 levels of classes.

Yoga Pose Detection and classification using deep learning

Analyzing the wisconsin breast cancer dataset using ml algorithms

Making cancer classification with knn module (Kaggle Expression)

Book recommender api written in flask framework

B.Tech final year project (Research Project)

Stock market analsis with python tools

A Python based project to train a Machine Learning model to detect different hand shapes in real time with multi-threading, using Computer Vision, to control the PC.

Exploring Recommender Systems using various Machine Learning Models like scikit-learn, Surprise, NLP and collaborative filtering using KNN and Tensorflow.

Loss J's statistical machine learning course. 🚀

Personalized book recommendation system for a user.Similar to Goodreads.

Applying Naive Bayes Algorithm to determine if breast cancer is benign or malignant

For this project, we'll be using a non-parametric classification method, k-nearest neighbors algorithm, to compress images.

This project implements the K-Nearest Neighbors (KNN) algorithm for classification purposes. KNN is a simple and effective algorithm for classifying data points based on their similarity to other data points in a given dataset.