Inspiration
Welcome to the future of culinary exploration! Our personalized recipe app is not just a collection of recipes; it's a culinary companion designed to elevate your cooking experience to new heights. Inspired by the desire to make cooking an enjoyable and tailored adventure, we have combined cutting-edge machine learning algorithms with an innovative swipe-based video system to create a one-of-a-kind platform.
The inspiration behind our project is rooted in the recognition that traditional recipe recommendation system fall short of meeting the diverse and evolving needs of home cooks. We understand that every individual has unique tastes, dietary preferences, and skill levels in the kitchen. Our goal is to empower users to discover recipes that not only align with their preferences but also cater to their culinary expertise.
We also solve to ever lasting question of when to eat what.
What it does
Imagine a world where every recipe recommendation is tailored precisely to your tastes. Our machine learning algorithms analyze your culinary history, preferences, and dietary requirements to curate a personalized selection of recipes that resonate with you. No more guessing which recipe might suit your mood or dietary restrictions – our app ensures that every dish is a perfect match for your palate.
Our algorithm learns from the user, who is effortlessly sending feedback through our video exploration feed.
But we didn't stop at personalization. We understand that life can be hectic, and scheduling your culinary adventures is not always straightforward. That's why our app allows you to effortlessly plan your meals. Whether you prefer a hands-on approach to scheduling or want the convenience of automatic planning, we've got you covered. With the ability to schedule recipes manually or let the app intelligently plan based on your preferences, you can take control of your kitchen without the hassle.
How we built it
Here's the tech stack:
Frontend: React, TypeScript, IONIC, SCSS, Vite, Node Backend: Django (REST-API), Postgresql (Database), Numpy, Scikit-learn (Recommendation-engine) Dataset: https://www.kaggle.com/datasets/elisaxxygao/foodrecsysv1
Prototyping and modelling was done in Figma.
Challenges we ran into
Time pressure, setting hard proirities,
Accomplishments that we're proud of
We are super proud to have build an application, that is not just another challenge, but something that each one of us will actually use after, making our lives easier. We are proud to make this available to others, helping them, finding recipes personalized to their unique interests.
What we learned
HackaTUM was a transformative experience for our team at FreshHub, pushing the boundaries of innovation and collaboration. Throughout this exhilarating hackathon, we delved into the intricacies of application development, honing our skills and adapting to challenges with agility.
The key takeaway was the power of synergy. As we worked tirelessly to build the FreshHub application, the diversity of perspectives within our team became our greatest strength. Each member brought a unique set of skills, ideas, and problem-solving approaches to the table, creating a melting pot of creativity that fueled our progress.
What's next for FreshHub
FreshHub is gearing up for an exciting evolution! Building on our foundation of individually recommending recipes, our next steps involve pushing the boundaries of personalization. We're enhancing our algorithms to dive deeper into your unique culinary profile, ensuring that each recipe suggestion is a perfect match for your tastes and preferences.
But that's just the beginning. We're working on features that go beyond recommendations – think intuitive meal planning tools and smarter organization options. Our aim is to make your kitchen experience not just personalized, but also seamlessly organized and effortlessly enjoyable. Stay tuned for the next wave of FreshHub, where your culinary journey becomes even more tailored and delightful.
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