Christiana U.

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Machine learning

AI Automation

Chatbots

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Freelancer Overview

I developed an efficient phishing website detection plugin using machine learning technique while using existing web browsers in critical online transactions. I gathered dataset consisting of 11,000 data points with 30 features downloaded from phishtank. This model was designed using random forest machine learning classifier and trained with 90% (9,900) of the dataset and tested with 10% (1,100) using Python programming language for better efficiency. Microsoft Visual Studio Code, Jupiter Notebook, Anaconda Integrated Development Environment, HTML/CSS and JavaScript was used in developing the frontend of the model for easy integration into existing web browser. I modeled it using use-case and sequence diagrams to test its internal functionalities. The result revealed that the proposed model had an accuracy of 96%, error rate of 4%, precision of 97%, recall value of 99% and f1-score of 98%.

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