Movie Sentiment predictor using decision tree classifier and random forests.

A data analysis report on ligand crystallography

Predicting the damage done to a building based on the data using Random Forest Classifier and XGBoost

Decision Tree Classifier and Boosted Random Forest

Data Analysis project analyzing the characteristics of credit card borrowers. After the analysis, a classification model is built.

Determine the most significant protective and risk factors when it comes to identifying the prevalence of cardiovascular disease in a patient

By using the ratios of various nutritional values ​​as data, it is aimed to find out which foods are closer to animal, vegetable or mixed food types. Using various supervised and unsupervised classification models, the efficiency of these models was evaluated by looking at the F1-score values.

Data engineering and machine learning operations

Presento el enfoque que utilicé en la competencia para predecir el estado de las bombas de agua en Tanzania.

EDISS Winter School 2024 Hackathon

This project is a machine learning model that predicts the next event type in the game Egg, Inc. based on historical event data.

The goal is to create a machine learning model that can identify individuals with diabetes based on specific criteria.

This is the second task in my internship with Codsoft about movie ratings prediction

Different ML Algorithms both in scripts & Jupyter Notebooks

This repository contains two sample implementations of the traditional Computer Vision task, Digit Recognizer from Kaggle. The URL of the dataset and relevant information can be found here: https://www.kaggle.com/c/digit-recognizer

Predicting if a system is vulnerable for malware. Analysis on different models.

A Machine Learning Model to predict Heart Diseases with the help of Framingham Data Set

Using supervised machine learning models to assess credit risk using Python

This is my version of analysis of Zomato Bangalore Dataset