Discord Archive Hub

Using Python, Flask, SQLAlchemy, Discord API

• Built a Flask-based website that stores documents and links via a Discord bot, featuring user login and registration.

• Utilized SQLAlchemy for data management, with CRUD (Create, Read, Update, Delete) capabilities for adding, deleting, and editing stored information, displayed dynamically on the website.

Demo

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Leguage of Legends Champion Recommendation System

Using Python, Flask, RIOT API, AWS Services

• Developed a champion recommendation system for professional tournament ban/pick phases, featuring algorithms for Counter and Synergy matrix calculations.

• Automated champion and match data updates via RIOT API, triggered through AWS Lambda and Event Bridge.

• Deployed the system on AWS EC2 with a Flask backend for efficient and scalable web service management.

Demo

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Netflix Movies and TV Shows Recommendation System

Pandas, Numpy, RapidAPI, Streamlit

• A website providing movie recommendations using a content-based recommendation system.

• Processed Netflix movie data from Kaggle utilizing TF-IDF and Bag of Words techniques for natural language processing. Implemented Similarity Score matrices to identify movies with akin content descriptions.

• Developed a website using Streamlit, incorporating RapidAPI’s Netflix Unofficial API for efficient movie image retrieval.

Demo

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Twitter US Airline Sentiment Analysis

Using Pandas, Numpy, Scikit-learn, Matplotlib, Seaborn

• Analyzing customer attitudes towards airlines in the United States based on a Twitter dataset using Natural Language Processing and Machine Learning techniques..

• Applied NLTK for data processing and vectorization, and addressed label imbalance with up-sampling.

• Developed a Random Forest model, tuning hyperparameters via Grid Search CV and Random Search CV, to predict customer attitudes and estimate model accuracy.

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