Projects
PHISHING WEBSITE DETECTION USING DEEP NEURAL NETWORK MODELS
The impact of phishing attacks is significant, with businesses in the United States losing up to $2 billion per year as their clients fall victim to these attacks. This project aims to develop a deep learning model for detecting phishing websites by extracting Uniform Resource Locator (URL) features. A diverse dataset containing labeled samples of phishing URLs and legitimate URLs will be collected and used to train the model. By analyzing and extracting URL features and patterns, the model will be trained to accurately identify and classify phishing websites.
Github
DISASTER TWEETS DETECTION
As social media has become an important part of many people's lives for keeping in touch with their friends and family, it has also become a crucial communication channel during times of emergency. It allows individuals to announce observed emergencies in real-time. This project aims to monitor, analyze, and determine which tweets are or aren't related to disasters.
Github
CANCER DETECTION USING PATHOLOGY SCANS
Pathology scans play a crucial role in cancer diagnosis, as they provide detailed visual information about tissue samples. However, manual analysis of these scans is time-consuming and prone to human error. This project addresses these challenges by employing machine learning techniques to automatically detect potential cancerous regions within pathology images.
Github
BBC NEWS CLASSIFICATION
With the continuous influx of news articles, it becomes essential to classify and organize them for effective information retrieval. This project addresses this need by employing machine learning algorithms to automatically categorize BBC News articles into various topics.
Github
COUNTRY CATEGORIZATION BASED ON DEVELOPMENT
The project aims to develop a tool that is designed to classify countries into different development categories using data from various development projects. This categorization aims to provide an understanding of a country's development progress by considering multiple dimensions of development, including economic, social, and environmental aspects.
Github
DIABETES PREDICTION MODEL
With the continuous influx of news articles, it becomes essential to classify and organize them for effective information retrieval. This project addresses this need by employing machine learning algorithms to automatically categorize BBC News articles into various topics.
Github
INTEREST RATE PREDICTION HACKATHON
Interest rates play a crucial role in the housing market. Lower interest rates can make housing more affordable, leading to increased demand and potentially higher property prices. Conversely, higher interest rates can have the opposite effect. This project utilizes machine learning techniques to predict interest rates for houses, incorporating various factors that influence these rates.
Github