Inspiration
Our AI-driven solution will use sophisticated algorithms to analyze the bestsellers, Goodreads choices, and Amazon Editor's picks in the specified genre to curate personalized book recommendations that match each user's tastes perfectly. With this system in place, you can say goodbye to endless browsing and effortlessly discover your next favorite book.
What it does
We wanted to create a platform that would make it easier for book enthusiasts to explore a wide range of recommendations tailored to their tastes, whether they're looking for comics, history novels, sci-fi or fantasy. Our platforms takes in user preferences such as category and price and then recommends reading material based on the input.
How we built it
We built our model by cleaning and pruning our data and fitting it to our model which we built using KNN.
Challenges we ran into
We ran into challenges combining the front end of our data (built on javascript) and back end (built using python).
Accomplishments that we're proud of
We are proud of how we worked together as a team to create our model.
What we learned
We learnt about different types of models that can be used to recommend and predict data.
What's next for BOOKWORMS
If given more time we can connect our front and back ends by using an API such as Flask to create an interactive site that users can use.
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