Ivan3864/SAFARIDINE-STAY-KENYA-THE-CULINARY-AND-LODGING-NAVIGATOR

Here is the presentation # SafariDine & Stay: Kenya's Culinary and Lodging Navigator ## Introduction "SafariDine & Stay: Kenya's Culinary and Lodging Navigator" is an innovative project that combines technology and gastronomy to create a personalized guide for travelers exploring Kenya. Using data and advanced machine learning, the system tailors recommendations based on individual tastes, budgets, and location preferences, ensuring a memorable dining and lodging experience. This project aims to celebrate Kenya's diverse culinary and hospitality landscape, simplifying the process of choosing restaurants and hotels while fostering a deeper connection between travelers and the nation's food culture and lodging options. It's a journey to offer the perfect plate and a cozy bed for every traveler's dream. ## Business Understanding ### Problem Statement Tourists in Kenya face the challenge of finding restaurants and hotels that align with their dining and lodging preferences, budget limitations, and desired locations. This results in subpar dining experiences and uncomfortable stays, ultimately hindering overall trip satisfaction. ### Key Components User Profile: Collects user data, including dining and lodging preferences, location, budget, and ratings. Restaurant and Hotel Databases: Store information on various establishments, including menus, cuisines, ratings, reviews, and pricing. Recommendation Engine: Uses machine learning to generate personalized recommendations. User Interface: Provides a user-friendly website or mobile app platform for interaction. ### Business Benefits - Improved Customer Experience - Increased Revenue - Enhanced Operational Efficiency - Data Insights ## Data Understanding Merging Restaurant and Hotel Data We've combined scraped data from TripAdvisor and Booking.com to provide a complete travel experience in Kenya. ### Data Sources - TripAdvisor (Restaurant Data) - Booking.com (Hotel Data) **Column Descriptions for the Combined Dataset** **id:** …