To build a classification methodology to predict whether a website is a phishing website on the basis of given set of predictors.
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Updated
Feb 12, 2022 - Jupyter Notebook
To build a classification methodology to predict whether a website is a phishing website on the basis of given set of predictors.
A ML project based on aqi data
This project classifies and detects malicious websites by analyzing various factors such as the URL of the website, IP address, the geographic location of where the website is hosted and other factors.
A simple program for classification of fruits on basis of color using KNN.
Steam is a video game digital distribution service with a vast community of gamers globally. A lot of gamers write reviews at the game page and have an option of choosing whether they would recommend this game to others or not. However, determining this sentiment automatically from text can help Steam to automatically tag such reviews extracted …
Explore my Kaggle competition solution repository for the year 2912. Join in to help rescue passengers trapped in an alternate dimension!
Classifying Wine Quality Data Based on Different Supervised Learning Methods - Logistic Regression, Decision Tree, Random Forest & Support Vector Machine.
Repo for machine Learning and Deep Learning Projects
Classification model to predict if the client will subscribe to a term deposit based on the given bank dataset
Implemented machine learning algorithms to analyze historical weather data
Classify iris plants into three species in this classic dataset
A deep learning model to classify Captcha images
Collaborated with Davies Biological Sciences Lab at the University of New Brunswick to automate the manual sorting of 45k shadowgraph images captured underwater in the Bay of Fundy for research purposes. Utilized computer vision and deep learning to develop an ensemble model that achieved a 94.42% accuracy rate, striking an optimal False Positive-F
Predicting Heart Disease using Machine Learning model
This is the repo for my fourth year Honour Thesis project repository
This project focuses on building a credit card fault detection model using machine learning techniques. The model aims to predict default payments based on various demographic and credit-related features.
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