🍳 Culinary Arts

BeautifulSoup

• Description: A library for pulling data out of HTML and XML files.

• Use Case: Scraping recipes, food blogs, and culinary reviews from websites for analysis and culinary research.

• Documentation: Beautiful Soup Documentation

• GitHub Repository: Beautiful Soup GitHub

FlavorNetwork

• Description: Based on a scientific study that presents a flavor network to understand and explore food pairings.

• Use Case: Analyzing and predicting flavor pairings and recipe component compatibility.

• Documentation: Flavor Network Research Paper

Matplotlib

• Description: A library for creating static, animated, and interactive visualizations in Python.

• Use Case: Visualization of culinary data, such as nutrition analysis, food trends, and culinary preference statistics.

• Documentation: Matplotlib Documentation

• GitHub Repository: Matplotlib GitHub

NumPy

• Description: Fundamental package for scientific computing with Python.

• Use Case: Numerical computations for nutritional data analysis and culinary science research.

• Documentation: NumPy Documentation
• GitHub Repository: NumPy GitHub

Pandas

• Description: Data analysis and manipulation library.

• Use Case: Organizing, analyzing, and manipulating culinary datasets such as ingredient databases and recipe collections.

• Documentation: Pandas Documentation
• GitHub Repository: Pandas GitHub

Pillow (PIL Fork)

• Description: The Python Imaging Library adds image processing capabilities to Python.

• Use Case: Image processing for culinary presentations, cookbook layouts, and food photography enhancement.

• Documentation: Pillow Documentation
• GitHub Repository: Pillow GitHub

Plotly

• Description: An interactive graphing library.

• Use Case: Creating interactive visualizations for culinary data, such as customer preference data or ingredient nutritional content.

• Documentation: Plotly Documentation
• GitHub Repository: Plotly GitHub

Scikit-learn

• Description: Machine learning in Python.

• Use Case: Predictive modeling for culinary trends, diet customization, and recipe recommendation systems.

• Documentation: Scikit-learn Documentation
• GitHub Repository: Scikit-learn GitHub

Seaborn

• Description: A Python data visualization library based on Matplotlib.

• Use Case: Creating attractive and informative statistical graphics in culinary studies and food science.

• Documentation: Seaborn Documentation
• GitHub Repository: Seaborn GitHub

spaCy

• Description: An open-source software library for advanced natural language processing.

• Use Case: Analyzing culinary text data, such as recipes and reviews, for insights into flavor profiles and culinary trends.

• Documentation: spaCy Documentation
• GitHub Repository: spaCy GitHub