AI-Powered Insights: Our advanced ML and Deep Learning models analyze a vast range of interview-related data to provide tailored insights for each user's needs. This includes commonly asked questions, industry-specific trends, and personalized suggestions for improvement.
Interview Simulation: Experience simulated interview scenarios with our AI assistant. Receive real-time feedback on your responses, gaze attention and emotions and improve your interview skills.
Industry Relevance: Whether you're pursuing a career in technology, finance, healthcare, or any other field, our AI assistant adapts its guidance to suit the specific requirements and expectations of your target industry.
Continuous Refinement: Our platform continually updates its insights and recommendations as interview trends evolve. This ensures that you're always equipped with the latest information and strategies to stand out in your interviews.
The following tech stacks were used in this product:
Frontend:
- ReactJS
- Tailwind CSS
- Sass
Backend:
- Flask
Machine Learning:
- Tensorflow
- OpenCV
- Python
Version Control:
- Git
- GitHub
UI/UX:
- Figma
We decided the plan of action and divided the wordload to go about in a systematic way and held frequent reviews amongst ourselves to check progress.
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The main issues we faced were finding the datasets for training our Deep Learning Models.
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Integrating the backend with the frontend.
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Deploying the models and integrating them with the backend.
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Non-Availability of compatible hardware and software for training our models.
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Deploment issues as integrating with the backend needed a paid version on Heroku.
We our proud of putting this project together as a team. It was a great experience for all of us to learn new tech stacks. A few things we overcome are:
- Increasing our CNN model's accuract from 26% to 77%.
- Building a backend using flask
- We learnt to work as a team in a systematic way.
- How to use Git efficently
- Integration and deployment of ML models on the website.
- UI/UX design
We plan to work on our machine learning models and complete the functionality of the features and work on the backend.