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Hotel Booking Demand Prediction

Technologies Used: GCP, Apache Spark, Docker, Hadoop

  • Leveraged Google Cloud Platform with Hadoop, Docker, and Apache Spark to process vast datasets, expedite data handling, and build machine learning models. Developed a Random Forest classifier attaining a 78% AUC-ROC, predicting booking cancellations.
  • Applied unsupervised learning techniques such as K-means clustering to segment the most profitable customers based on lead time and ADR (Average Daily Rate), influencing hotel profitability strategies.

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