Built feed-forward dense neural networks and convolutional neural networks to predict the speaker of an audio clip from 115 different speakers with a 99.8% accuracy and also predicted his/her gender with a 95% accuracy.
Used Google Street View, Google Geolocation and Zillow APIs to develop a flask web app to help FEMA in assessing property damage after a natural disaster
Built several binary classification models using Natural Language Processing (NLP) and reddit’s API to classify over 150k posts. Used tableau to visualize best models and parameters. Best model had an accuracy of 95% on validation data
Given data for house prices and about 80 features, I had to use my knowledge of python, pandas, matplotplib, seaborn, sklearn and others in order to generate accurate predictions and answer some business questions using statistical analysis.