This repository is a collection of programs implemented as part of Machine Learning Laboratory course at JSS Science And Technology University(SJCE).
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Updated
May 29, 2024 - Jupyter Notebook
This repository is a collection of programs implemented as part of Machine Learning Laboratory course at JSS Science And Technology University(SJCE).
In this work, an automatic and reproducible methodology is proposed using computer vision techniques for sorting oranges by size and defects. Master thesis written in Spanish.
Gretl implementation of the knn machine-learning algorithm
Clustering employee performances to predict resignation likelihood and develop strategies for employee retention
5 different kinds of machine learning alorithms has been used for the classfication of the animals and have been compared with each other
Ce projet est une proposition de solution au Rakuten Data Challenge. L'objectif est de mettre en œuvre différentes méthodes de Machine Learning et Deep Learning pour résoudre le problème.
Customer Attrition Prediction with Python
Some exercises codes on basics of machine learning built from scratch with basic libraries like numpy ,math.
Movie Recommendation System using Collaborative Method (User - User similarity , Item-Item similarity)
Machine Learning Notebooks for various Algorithms with data file
MATLAB Project
A Performance Study of Naive Bayes Classifier in Advertisement Analysis
A machine learning project using python aiming to benefit the banking industry and reduce the hassle, pressure and workload and increase the efficiency and effectiveness of the process of issuing loans
This project aims to build a complete pattern recognition system to solve classification problems using the k-Nearest Neighbors (KNN) algorithm. To classify chest X-ray images into three categories: COVID-19 positive, pneumonia positive, and normal. To achieve this, we utilize the COVID-19 Chest X-ray dataset available on Kaggle.
Breast Cancer Detection - This project tackles the crucial challenge of early breast cancer detection using machine learning techniques. Using Machine learnig algorithms, Support Vector Machine, Randon Forest.
A comprehensive project with scraping data, methodology, including graph construction, common subgraph identification, KNN implementation, and classification results.
A ML application(deployed on flask) to detect heart disease in patients based on medical features.
Classifier to detect false alarms in London Rescue Teams
Web Based application with various operations for data science
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