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Pixel_to_Plate_Flowchart

Description:

Step into a world where pixels meet palates, where your visual inspiration sparks culinary creativity! At the heart of "Pixel to Plate" lies a dynamic fusion of machine learning, computer vision, and deep learning techniques, all orchestrated to redefine how we interact with recipes.

Project Overview:

"Pixel to Plate" embarks on an exhilarating journey through the realms of artificial intelligence and culinary arts. By harnessing the power of ML and computer vision, we've crafted an innovative recipe generation system that transcends traditional boundaries.

Key Objectives & Ideas:

🍳 Recipe Scraping: Unveiling a treasure trove of culinary wisdom by scraping recipes and cooking-related content from the vast expanse of the internet.

📚 NLP Magic: Infusing recipes with linguistic finesse through the application of Natural Language Processing (NLP), allowing for seamless categorization and comprehension.

🔍 Visual Exploration: Leveraging the prowess of OpenCV for meticulous image analysis, unraveling the mysteries of ingredients and beautifully plated dishes alike.

🧠 Deep Learning Delight: Crafting a deep learning model that intuitively recommends recipes tailored to individual preferences and available ingredients, ensuring a personalized culinary experience.

🌐 Interactive Oasis: Building a vibrant web application that serves as an interactive hub for culinary enthusiasts, offering a visually captivating recipe recommendation system that dances to the beat of your taste buds.

Flowchart ML masterchef (2)

Join us on this exhilarating escapade, where every pixel holds the promise of a delectable journey from screen to plate! Let "Pixel to Plate" be your guiding star in the realm of gastronomic exploration! 🌟
Click Here to read the entire RESEARCH PAPER!

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In this repository, you find the content required for BDA 602 Machine Learning final project.

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