Inspiration
Problems:
- People can't decide what movie they want to watch
- Parents want age-appropriate movies for their children
What it does
The movie recommendation chatbot provides a movie recommendation based on the user's age and preferred genre.
How we built it
We built it using python in Google Colab, so it was made through a combination of data organisation and programming.
Challenges we ran into
We had to ensure that the dataset is comprehensive and accurate, such that the movie titles are properly categorised based on their genre and age ratings. Another challenge was overlapping age ranges. For example, a movie could be suitable for more than one age range. Thus, understanding the conditional statements was very important.
Accomplishments that we're proud of
The movie recommendation chatbot showcases our ability to create an interactive and personalised user experience, taking into account different age ratings and genre preferences. It demonstrates our skills in data organisation and logic implementation. We are also proud of how we learnt to use figma and make use of animations to create an accurate simulation of our chatbot.
What we learned
We learnt how to use while loops and conditional statements (if elif else) in python. We also learnt how to make decisions as coding and animating challenges us to think critically to come up with effective solutions. For example, our original idea/code involved the case where some genres were considered "inappropriate" for certain ages (eg below 13 can't watch horror), but we decided to make sure that there would be a movie title output no matter what age/genre is inputed (provided it is in the dictionary)
What's next for Movie Recommendation Chatbot
We can integrate with movie APIs to fetch real-time movie data, so that recommendations are more up to date and there is a more comprehensive dataset. We can also enhance the user interface of the chatbot by including more elements like movie trailers, pictures, ratings etc
Built With
- figma
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