Vast improvement and refactoring of the previous Pet Adoption Time project. Incorporated image feature extraction, image metadata, entity sentiment, and text mining to the initial model Skills: Python, Keras, LightGBM, Google Vision, Google NLP, Convolutional Neural Network, TF-IDF
Front-end web app visualizing and analyzing artists’ musical audio features through Spotify’s Web API. Identifies the most unique and the most ordinary tracks for an artist and provides recommendations for other similar songs
(Note: Please allow a few moments for Heroku to spin up the initial dyno)
Skills: Python, App Development, CSS, API, Data Visualization
Extracts deep image feature representations and merges the content of one image with the style of a second images Skills: Python, TensorFlow, Computer Vision, Convolutional Neural Network
Increasing profitability of a bakery through Association Rule Learning
Skills: R, Association Rule Learning, Market Basket Analysis
Predicting pet adoption time using a decision tree ensemble model Skills: Python, Supervised Ensemble Learning, XGBoost, Decision Trees, χ2 Analysis, EDA
Predicting polarity of user reviews through text mining of IMDB reviews without NLTK's SentimentAnalyzer library Skills: Python, NLP, Sentiment Analysis, Text Mining
An XGBoost ensemble model predicting house prices of the Boston real estate market
Skills: Python, Imputation, Regression, Feature Engineering, XGBoost, Ensemble Models
Predicting survival of passengers aboard the Titanic using binary classification machine learning Skills: Python, EDA, Feature Engineering, Imputation, Classification, Neural Networks