Maneesh Madala

Machine Learning based Flood Prediction

• This project involves creating a web-based application for flood prediction using machine learning.
• It utilizes historical data on rainfall and flood occurrences in a specific state, employing tools like SQLyog and Python. The application aims to forecast floods based on this data.

Customer Segmentation

• In this machine learning project, we used unsupervised learning, specifically the K-means algorithm, because our dataset lacked labels.
• The project's focus was on customer segmentation, and the tools used for this analysis were primarily R programming.

COLD CHAIN PRODUCT MONITORING USING WEB-BASED SUPPORT

• In this project, we focus on monitoring products within the cold chain using web-based support. Temperature control is critical for preserving perishable goods during logistics.
• We employ the decision tree algorithm to classify products based on various variables, aiding in labeling the unlabeled client data. This analysis assesses factors like freshness and quantity loss, ensuring proper cold storage conditions.
• Tools used include Eclipse, Heidi SQL, and the Apache Tomcat Server.