KeyWord Study

Inspiration

As a student, I often found myself struggling to keep up with the vast amount of information that was being thrown at me. I would spend hours reading and re-reading my notes, but I still couldn't seem to remember everything. I realized that I needed a better way to study, and that's how the idea for Keyword Study came about.

What it does

Keyword Study is a website prototype that extracts keywords with their meanings from any text input, storing them for later query. This makes it easy to quickly and easily review the most important concepts from a given text, without having to spend hours re-reading the entire thing.

How we built it

To build Keyword Study, I used a combination of natural language processing (NLP) and machine learning (ML) techniques. First, I trained an NLP model to identify keywords in text. Then, I used an ML model to extract the meanings of those keywords. Once I had a working prototype, I deployed it to a web server so that other students could use it.

Challenges we ran into One of the biggest challenges I faced was training the NLP model to identify keywords in text. There are many different ways to identify keywords, and it was difficult to develop a model that could accurately identify keywords in a variety of different contexts.

Another challenge was extracting the meanings of keywords. Many words have multiple meanings, and it was important to develop a model that could accurately identify the correct meaning of a keyword in a given context.

Accomplishments that we're proud of

I am proud of the fact that I was able to develop a working prototype of Keyword Study in a relatively short amount of time. I am also proud of the fact that Keyword Study is easy to use and can be used by students of all skill levels.

What we learned One of the most important things I learned while developing Keyword Study is the importance of data quality. The NLP and ML models that I used are only as good as the data that they are trained on. I spent a lot of time cleaning and preparing my training data, which made a big difference in the performance of my models.

Another important thing that I learned is the importance of feedback. I had several other students test out my prototype and give me feedback. This feedback was invaluable in helping me to improve Keyword Study.

What's next for EduBuddy

I plan to continue developing Keyword Study and make it even more useful for students. I am also interested in exploring other ways to use NLP and ML to help students learn more effectively.

Built With

• llama-index
• openai
• python
• streamlit