This project explores loan data to identify trends and insights that can help in understanding lending patterns, borrower behavior, and risk factors. By using Python and Jupyter Notebook, the project analyzes factors like borrower demographics, credit scores, loan purposes, and default rates to create a detailed view of loan performance.

This is a sophisticated app designed to analyze financial datasets and uncover market trends. Leveraging powerful tools like Python, Pandas, and Scikit-learn, this app offers deep insights into stock performance, helping investors and analysts make informed decisions. Explore data-driven strategies and stay ahead in the financial market.

Diwali-Sales-Analysis-Project

The "kidney-stones-Detector" is an advanced system delivering precise detection and classification of kidney conditions including stones, cysts, tumors, and normal states from medical imaging data. With an impressive accuracy of 98.87%, this machine learning-powered models offer reliable insights for medical professionals.

Linea De Enfasis Ciencia de Datos y Machine Learning

Learning Python For Data Engineering

A Capstone Project on Makaan Property Analysis by Machine Learning.

A case study on Weather Analysis during World War 2 by Machine Learning.

East West Airlines Analysis by Clustering.

Crime Data Analysis by Clustering.

Travel Data Analysis by ARIMA.

Fraud Check Analysis by Random Forest.

Company Data Analysis by Random Forest.

Data Analysis of iPhone Purchase Records by Decision Tree.

Data Analysis of Bank by Logistic Regression.

Data Analysis of iPhone Purchase Records by KNN.

Predict salary of new employee by Polynomial Regression.

Bangalore House Price Prediction by KNN

Prediction model for Insurance Cost dataset by Regression