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Above the fold
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Below the fold
✨ Inspiration
- As an avid anime fan, I've often found it challenging to discover new and exciting anime series to watch. To address this issue, I embarked on the journey to create ARES (Anime Recommendation Engine - Streamlit), a personalized recommendation system that helps anime enthusiasts like myself discover hidden gems in the vast world of anime.
What it does
- ARES leverages a vast dataset containing information on over 19,000 anime titles to provide users with some good once. (dataset taken from kaggle : https://www.kaggle.com/datasets/marlesson/myanimelist-dataset-animes-profiles-reviews)
🚀 How we built it
- We took the dataset from Kaggle, which included essential details such as title, synopsis, rating, and image URLs for each anime. Using Python and the Streamlit framework, we developed an intuitive and user-friendly interface.
👨💻 Challenges we ran into
Some of the hurdles we faced included:
It was my first time using python and it's respective libraries like numpy and pandas which was a bit tricky since there was a lot of new syntax but it was fun as well!!
Integrating CSS with Streamlit: Creating an aesthetically pleasing and engaging user interface required mastering the integration of CSS styles within the Streamlit environment.
Utilizing Pandas and Numpy: While these libraries are powerful tools for data manipulation, they posed a learning curve for me as I delved into their functionalities.
Despite these challenges, overcoming them added valuable skills to our arsenal and enhanced the project's overall quality.
🎯 What's next for ARES
The journey doesn't end here. We have exciting plans for ARES's future, including:
More Customization: Empowering users with additional customization options, such as filtering anime by the range of episodes, genre preferences, rankings, and more.
Enhanced Machine Learning: Implementing advanced machine learning algorithms to continuously refine and personalize recommendations based on user feedback.
Community Engagement: Building a vibrant anime-loving community where users can share their favorite series, reviews, and recommendations.
With ARES, we aim to make the anime discovery experience not only effortless but also incredibly enjoyable. Stay tuned for more exciting updates!
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