Keywords: Hotel, Booking
The project's objective is to utilize deep learning techniques to predict hotel booking demand. By analyzing historical booking data, it aims to develop a model capable of accurately forecasting future booking patterns. This predictive tool could assist hotels in optimizing resource allocation, enhancing guest satisfaction, and efficiently managing bookings. The project emphasizes the value of applying DL methods to address the challenges of predicting hospitality industry demand and improving customer experiences through data-driven insights.
Aim
To demand the Booking of Hotel Using DL Techniques
Objective
Predict hotel booking demand using DL techniques. Train model with booking data for accurate forecasts. Validate the model's efficacy in anticipating hotel booking demand through DL methods.
ANN Technique used
Jupyter, Google Collab
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