Inspiration
The inspiration for this project came from the need for a more efficient way to analyze feedback from hackathons. The traditional method of manually filtering through feedback forms is time-consuming and often results in missed insights.
What it does
SentiHack is an NLP project that uses Azure Cognitive Services API to determine the sentiment of feedback received in hackathons. The project provides an overall score for each piece of feedback, which varies between 0 & 1 where 0 shows the negative and 1 shows the positive feedback. It will help Hackthons organization to quickly and efficiently analyze the feedback and make improvements based on negative feedback.
How we built it
The project was built using NLP techniques and the Azure Cognitive Services API. The API was integrated into the project to provide sentiment analysis capabilities, while the NLP techniques were used to process the feedback and provide the overall score.
Challenges we ran into
One of the challenges faced while building the project was ensuring the accuracy of the sentiment analysis. To overcome this, extensive testing was carried out to fine-tune the model and ensure accurate results.
Accomplishments that we're proud of
I am proud of the fact that I was able to develop an efficient and effective solution for analyzing feedback from hackathons. The project has the potential to save MLH a significant amount of time and effort while providing valuable insights into the experiences of hackathon attendees.
What we learned
I learned about the various NLP techniques and the power of the Azure Cognitive Services API in sentiment analysis. I also learned about the importance of fine-tuning the model to ensure accuracy and the benefits of automating manual processes.
What's next for SentiHack
In the future, I plan to further improve the accuracy of the sentiment analysis and add new features to the project to make it more comprehensive. I am working on making the project more user-friendly and accessible to a wider audience.
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