Thangarasu's Projects
Through this project, we aim to provide a comprehensive understanding of the dynamics driving the stock prices of Amazon, Domino's Pizza, Bitcoin, and Netflix.
About This project aims to provide insights into the factors influencing employee attrition and predict which employees are likely to leave the company.
To analyze the CFPB complaint data to identify trends, patterns, and insights that can inform business decisions and improve consumer protection.
The "Industrial Copper Modeling" project is designed to enhance your proficiency in data analysis and machine learning, focusing on the challenges posed by complex sales and pricing data in the copper industry. This hands-on project employs advanced machine learning techniques to provide solutions, offering regression models for precise pricing pre
The Food Price Estimation project focuses on providing estimates of food prices to capture local price fluctuations in regions where people are vulnerable to localized price surges. The project utilizes a machine-learning algorithm designed to predict ongoing subnational price surveys, demonstrating accuracy comparable to direct price measurements.
Through this FMCG Sales Exploratory Data Analysis (EDA) project, we aim to provide actionable insights that can drive business decision-making and enhance performance within the FMCG industry
The Resale Flat Price Prediction project aims to tackle the challenges associated with accurately estimating resale flat prices in the competitive Singapore market. In a dynamic real estate landscape, predicting resale prices is a crucial task that benefits both buyers and sellers, enabling them to make informed decisions.
Contributed to the improvement of risk management practices in the lending industry. Led to more responsible lending practices and reduced financial risks
Sessions on Object Oriented Programming Concepts using Python for GUVI
In the real estate industry, the determination of rental prices plays a critical role in shaping the interactions between property owners, tenants, and property management companies. The ever-changing nature of the real estate market necessitates a dynamic and data-driven approach to set competitive and fair rental prices.
Config files for my GitHub profile.
The Used Car Price Prediction project aims to develop a robust data science solution for accurately predicting used car prices. Leveraging a diverse dataset encompassing essential features like car model, number of owners, age, mileage, fuel type, kilometers driven, additional features, and location, this project aspires to build a powerful machine