Disaster Response Web Application is a Web app that can help emergency organizations analyze incoming messages and classify the messages into specific categories (e.g. Water, Food, Hospitals, Aid-Related) during a disaster event. The app is based on Nature Language Processing and Random Forest Classifier ML model. The data was collected by Figure Eight and provided by Udacity.
A tool can speed up your data analysis
The goal of this project is utilizing unsupervised machine learning to identify target segments.
Say goodbye to my old website.
A project of using Machine Leaning to identify potential donors.
This is an introduction to my Python Script that automates image processing.
Spam is still a common attack method. Most of the email services have spam filters that can help us block and filter out most of the emails with commercial, fraudulent and malicious content. The purpose of the project is to explore and analyze the email header to identify the features that can tell us which emails are malicious.
Spam is still a common attack method. Most of the email services have spam filters that can help us block and filter out most of the emails with commercial, fraudulent and malicious content. The purpose of the project is to explore and analyze the email header to identify the features that can tell us which emails are malicious.
