Repository to store code and study material for the Internship

Using Classification Techniques, Data reprocessing, Feature Engineering, Feature Extraction and Classification Algorithms from Machine Learning to Predict who can Survive the attack of Tsunami. Data Description

Kickstarter Campaign Success Prediction with ML Classification Algorithms

For this group project, I performed cluster analysis and classification using Python to predict one of three classes for water pumps; functional, functional but needs repair, and non-functions. I used clustering to find hidden data structures to exploit for fitting individual classification techniques with better results than using the entire da…

The project deals with predicting the number of persons killed based on the contributing factors such that necessary precautions and actions can be taken in order to avoid the accidents and reduce the death rates and injuries of the person in the New York city.

This is a Machine Learning model designed to analyze various factors that contribute to Employee Turnover including job satisfaction, last evaluation, number of projects, average monthly hours, time spent in company, accidents at workplace, promotion in 5 years, department and salary.

Content maturity rating method for artistic social communities

Use of classification supervised learning algorithms as a tool to perform predictive analysis over whether a mammogram mass is benign or malignant

Detection and Recognition of faces using ML Classification Algorithms, Neural Networks, Siamese Network and face-recognition library at Python

LENS: Learning ENSembles using Reinforcement Learning 2017 (v1.0)

This project aims to develop a machine learning model that can accurately classify an individual's credit score between ["Good", "Standard","Poor"]. The model was trained using a supervised learning algorithm, Random Forest, on a dataset of credit score data.

A Python GUI project to compute the results of Data Mining Classification Algorithms: Naive Bayes & ID3 Decision Tree.

This repository includes python code to check various Machine learning classification algorithms like KNN, Decision Tree, SVM and Logistic regression. It compares accuracy of different classification algorithms with jaccard_score, F1_score and log_loss.

Predicting Mountain Goats Album Era with Sentiment Analysis

This repo contains machine different learning algorithms.

Identify a list of customers who will subscribe to Term Deposit Account using the classification problem

This repository serves as a storage space for classification projects. Organized by projects, each directory houses code files, documentation, and dataset necessary for running and understanding the project. Feel free to explore the projects. Reach out for inquiries, feedback, or collaboration opportiunities.