Web scraping to gain company insights. Scraping and analysing customer review data to uncover findings for British Airways
A proof of concept for a WEB API that predicts cart abandonment based on real-time customer behaviour data.
This Jupyter Notebook implements Bayesian modeling techniques to fit a posterior distribution and forecast demand for an e-commerce company.
Churn Shield empowers B2B companies to: Predict customer churn in real-time using machine learning Analyze retention risks through an interactive dashboard Make data-driven decisions with stakeholders
ML pipeline using Logistic Regression to predict customer purchase intent. Involves data preprocessing, model training, hyperparameter tuning, and evaluation, aimed at helping businesses understand customer behavior and optimize sales strategies.
RFM-based feature engineering and regression modelling to analyse and predict customer behaviour.
A virtual internship program in Forage. For British Airways, As a first part, web scraped customer reviews from SkyTrax and analysed sentiments of the reviews. As a second part, analysed customer behavior data to predict if they complete booking a flight.
Predicting hotel booking cancellations using machine learning to identify high-risk reservations and reduce revenue loss
ML model to recommend Megaline plans (Smart vs Ultra) using customer behavior data. Achieved 0.81 accuracy with Random Forest.
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