The problem Syllabuster solves

The AI-powered web app solves a common problem that students face during exam preparation. Oftentimes, students have limited time to prepare for exams and struggle to identify the most important topics to focus on. Sorting through question papers and trying to understand which topics are crucial can be a daunting task, and this can lead to anxiety and stress for students.

The web app solves this problem by leveraging the latest OCR and AI technologies to automate the process of identifying important topics. The app can analyze the syllabus and use OCR to convert question papers to text. It then uses NLP, TensorFlow, and OpenAI modules to generate a question bank based on the identified important topics.

The question bank is a diverse set of questions that students can practice, helping them to better understand the topics and improve their problem-solving skills. This can be particularly helpful for students who may not have access to a wide range of study materials.

Additionally, the web app provides relevant study materials and YouTube links, which can help students to access resources more easily and study more efficiently. This can save students a significant amount of time and effort in trying to find relevant study materials on their own.

Overall, the web app can help students to prepare for exams more effectively and comprehensively, ultimately improving their performance and reducing their stress and anxiety. By automating the process of identifying important topics and providing a diverse set of questions and study materials, the app can help students to study smarter, not harder.

**Key Features:

1. generate a question bank based on the identified important topics.
2. automate the process of identifying important topics
3. AI technology to analyze syllabus and exam pattern
4. Provides additional practice questions
5. Easy access links to youtube videos of important topics**

Challenges we ran into

When I started developing my web app, one of the challenges I encountered was that the text in the images I was working with was not directly accessible. This meant that I had to find a way to extract the text from the images so that I could use it in my app. I tried several OCR tools to achieve this, but it was difficult to find one that could accurately extract the text from the images. It took some time and effort, but eventually, I was able to find the best OCR tool for my needs.

Another challenge I faced was with the question sorting module. Initially, I tried classifying the questions with words, but I was not getting the desired results. I realized that the questions were too complex to be sorted based on simple keywords. So, I turned to NLP to sort the questions based on their meaning, and this worked much better. With the questions sorted, I was then able to use the OpenAI API to further enhance the functionality of my app.

Developing software always involves unexpected challenges, and it can be frustrating when things don't work as expected. However, I learned that the ability to adapt and find solutions is critical to overcoming these challenges. In the end, I was able to create an awesome program that works great and surely everyone in our college is gonna use it for exams