Tushar

PROJECTS PhonePe Sentiment Analysis - Tools Used- Python (Spacy, NLTK), Data Visualization, Feature Engineering - Web Scraping, Data Cleaning, Data Analysis, Data Visualization, Classification, Sentiment Analysis - Imported 40000 data into python from Google play store, Apple play store, and twitter API on PhonePe. - Classified the data into 3 categories. i.e. reviews related to payment, AppUI and Offer - Performed Sentiment Analysis using Vader and Classified reviews into Positive, Negative, or neutral ones. Predicting the price of new user booking (Airbnb) - Tools Used- Python, Machine Learning - Data Preprocessing, Data visualization, and EDA - Predictive Modeling, Linear regression, Lasso, Ridge, LGBMR - Trained the dataset using LGBMRegressor algorithm - The model performed with an R-square of 0.82. Predicting Medical Appointment - Tools Used- Python, Machine Learning - Data cleaning, Data Preprocessing, Data Visualization, EDA - Predictive Modeling, Logistic regression, Random Forest Classifier, LGBMClassifier, XGBClassifier - Trained the dataset using Logistic Regression algorithm - The model performed with an accuracy of 89.91%.