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"FoodieSpotter is a Python project that uses data analysis and visualization to explore and recommend diverse cuisine options across Massachusetts. By clustering eateries based on location and cuisine type, it helps users discover exciting dining experiences tailored to their tastes."

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Applied_Data_science_Capstone

FoodieSpotter: Discover Your Next Food Adventure

Project Description: FoodieSpotter is your go-to companion for embarking on delightful culinary journeys across Massachusetts. If you're a food enthusiast and want to explore new flavors and dining experiences, this personal project is designed just for you. Using data science techniques, FoodieSpotter helps you uncover hidden gems, popular cuisines, and exciting restaurants in different neighborhoods.

Project Goals: The main objectives of FoodieSpotter are:

  • Neighborhood Exploration: Uncover local dining options and vibrant food scenes across Massachusetts.
  • Cuisine Diversity: Discover a wide range of cuisine types that cater to various tastes and preferences.
  • Visual Insights: Utilize data visualization to make informed decisions about where to indulge in your next food adventure.

Data Sources:

  1. Local Zip Codes: A dataset containing zip codes, city names, and state names for Massachusetts.
  2. Venue Details: The Foursquare API provides venue information, including restaurant categories, ratings, and reviews.

Methodology:

  1. Data Collection and Preprocessing: Gather zip code data and utilize the Foursquare API to collect venue details.
  2. Exploratory Data Analysis: Visualize venue distributions and popular cuisines to gain insights into the local food scene.
  3. Cuisine Exploration: Analyze cuisine types and identify the most common and unique options.
  4. Interactive Mapping: Utilize geospatial visualization to map out restaurant locations and explore neighborhoods.
  5. Personalized Recommendations: Provide suggestions based on preferred cuisine and location preferences.

Project Benefits:

  • Food Discovery: Discover new eateries, cafes, and restaurants that align with your culinary interests.
  • Local Insights: Gain a deeper understanding of dining options in different areas of Massachusetts.
  • Personalized Experience: Receive tailored recommendations based on your preferences and desired experiences.

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"FoodieSpotter is a Python project that uses data analysis and visualization to explore and recommend diverse cuisine options across Massachusetts. By clustering eateries based on location and cuisine type, it helps users discover exciting dining experiences tailored to their tastes."

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