AloRay

CREDIT-CARD-FRAUD

This project focuses on building a fraud detection model for credit card transactions using a dataset containing transactions made by European cardholders in September 2013. We are working with a highly unbalanced dataset and the challenge lies in effectively detecting fraudulent transactions while minimizing false positives.

CREDIT-RISK-PREDICTION

Model selection crucial in loan approval prediction project. Random Forest outperformed Logistic Regression, emphasizing importance of choosing appropriate models for accurate predictions.

CUSTOMER-SEGREGATION-K-MEANS-

Customer Segmentation using K-Means clusters customers based on spending habits, age, and income. This helps target marketing strategies, improve customer understanding, and maximize profits through tailored approaches.

GAS-PRICE-FORECASTING

This repository utilizes time series analysis to predict natural gas prices, aiding informed decisions in the energy market. Through meticulous data preprocessing, visualization, and ARIMA modeling, it provides accurate forecasts. With regression and interpolation techniques, it offers deeper insights for stakeholders, enabling proactive strategies

linear-regression-and-price-prediction

using linear regression to predict price of used cars

portfolio

PREDICTING-CREDIT-RISK

Logistic Regression and Random Forest classifiers are used to create a machine learning model that attempts to predict whether a loan from LendingClub will become high risk.

STOCK-PREDICTION-WITH-PYTHON

We utilize LSTM networks to forecast Microsoft Corporation's stock prices. We gather comprehensive historical data, preprocess it, construct LSTM models, train and evaluate them, and provide future price predictions.

TIME-SERIES-ANALYSIS-AND-FORECASTING-SUPERSTORE-DATA

This project analyzes and forecasts Superstore sales data for furniture and office supplies using time series models like ARIMA and Facebook's Prophet, highlighting seasonal patterns and trends.

twitterdataextraction

using twitter data to analyze celebrity popularity

AloRay/GAS-PRICE-FORECASTING

This repository utilizes time series analysis to predict natural gas prices, aiding informed decisions in the energy market. Through meticulous data preprocessing, visualization, and ARIMA modeling, it provides accurate forecasts. With regression and interpolation techniques, it offers deeper insights for stakeholders, enabling proactive strategies

AloRay/portfolio

AloRay/CREDIT-CARD-FRAUD

This project focuses on building a fraud detection model for credit card transactions using a dataset containing transactions made by European cardholders in September 2013. We are working with a highly unbalanced dataset and the challenge lies in effectively detecting fraudulent transactions while minimizing false positives.

AloRay/CREDIT-RISK-PREDICTION

Model selection crucial in loan approval prediction project. Random Forest outperformed Logistic Regression, emphasizing importance of choosing appropriate models for accurate predictions.

AloRay/CUSTOMER-SEGREGATION-K-MEANS-

Customer Segmentation using K-Means clusters customers based on spending habits, age, and income. This helps target marketing strategies, improve customer understanding, and maximize profits through tailored approaches.

AloRay/linear-regression-and-price-prediction

using linear regression to predict price of used cars

AloRay/PREDICTING-CREDIT-RISK

Logistic Regression and Random Forest classifiers are used to create a machine learning model that attempts to predict whether a loan from LendingClub will become high risk.

AloRay/STOCK-PREDICTION-WITH-PYTHON

We utilize LSTM networks to forecast Microsoft Corporation's stock prices. We gather comprehensive historical data, preprocess it, construct LSTM models, train and evaluate them, and provide future price predictions.

AloRay/TIME-SERIES-ANALYSIS-AND-FORECASTING-SUPERSTORE-DATA

This project analyzes and forecasts Superstore sales data for furniture and office supplies using time series models like ARIMA and Facebook's Prophet, highlighting seasonal patterns and trends.

AloRay/twitterdataextraction

using twitter data to analyze celebrity popularity