🚀 Software Developer | Passionate Creator | Impact Seeker
🌟 With over a year of software development experience, I thrive on turning innovative ideas into impactful projects that touch people's lives.
🛠️ From crafting elegant code to building solutions that make a difference, I'm dedicated to creating technology that drives positive change and empowers communities.
💡 Let's collaborate on projects that inspire and transform. Together, we can make a difference, one line of code at a time.
📫 Reach out to me for exciting opportunities and meaningful collaborations!
✨ Let's build a better tomorrow, today! ✨
- [Tech Stack] -
- Engineered a cloud-native user management system deployed on Google Cloud Platform (GCP).
- Implemented automated deployment of Node.js APIs using GitHub Actions, streamlining the CI/CD pipeline.
- Utilized Packer and Terraform for infrastructure as code, ensuring consistent and reproducible deployments
- Implemented unit and integration tests using Jest, Mocha, and Chai.
- [Tech Stack] -
- Developed a medical image generation system using advanced deep learning techniques.
- Fine-tuned the CLIP component of a diffusion model to generate images of skin diseases from textual prompts.
- Implemented a user-friendly interface using Streamlit for easy interaction with the model.
- [Tech Stack] -
- Implemented a Text Summarizer project utilizing Large Language Models (LLMs) to condense conversation into precise summary.
- Leveraged pre-trained pegasus LLM from hugging face transformers to fine tune samsum dataset.
- [Tech Stack] -
- Developed a deep learning model to classify facial expressions into 7 emotion categories (angry, disgusted, fearful, happy, neutral, sad, surprised).
- Utilized a Convolutional Neural Network (CNN) architecture trained on the FER-2013 dataset, achieving 63% accuracy on the test set.
- Implemented real-time emotion detection using OpenCV for face detection and the trained model for classification.
- [Tech Stack] -
- Developed and compared three models Logistic regression, Decision Tree and Random forest respectively.
- Performed feature selection, exploratory data analysis and model evaluation.
- Addressed imbalanced classes, showcasing the unbiased nature of Tree based classifiers.
- [Tech Stack] -
- Developed RESTful APIs using the Django framework to augment API performance and implemented personality prediction utilizing K-means clustering. Achieved an accuracy rate exceeding 80% through analysis of DASS (Depression, Anxiety, and Stress Scale) test data.
- [Tech Stack] -
- A Doctor - Patient Management Portal in which patient has ability to schedule an appointment with doctor.
