Machine Learning Engineer | MLOps Enthusiast
I am Pramit De, a final-year Computer Science student passionate about Data Analysis, Machine Learning, and deploying AI applications.
My journey into data science began with uncovering hidden patterns through EDA, like detecting a hurricane from New York taxi data. This curiosity drives me to solve real-world, business-focused problems through practical projects and internships.
- Developed a MobileNetV2-based model with transfer learning to classify food ingredients for recipe automation and inventory management.
- Achieved 93.14% test accuracy through hyperparameter optimization using Keras Tuner.
- GitHub Repository
- Built a Streamlit app using Google GEMINI 1.5 Pro API to generate customizable comprehension exercises.
- Implemented a review-generation chain to ensure high-quality outputs.
- Deployed on AWS EC2 with 20-second average response time for optimized user experience.
- GitHub Repository
- Designed a chatbot to recommend recipes based on ingredients and preferences, providing personalized cooking assistance.
- Used a Retrieval-Augmented Generation (RAG) model using cookbooks and Wikipedia data.
- Deployed as a FastAPI app on AWS EC2 with optimizations for faster response times and efficient memory management.
- GitHub Repository
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Programming Languages & Tools:
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Python Libraries:
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Databases:
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Core Concepts:
Data Wrangling ,EDA, Statistical Modeling, Machine Learning, Deep Learning
- Business-oriented
- Team player
- Problem-solving
- Strong communication skills
I’m currently expanding my knowledge in:
- MLOps: To improve model deployment, monitoring, and CI/CD for efficient model management in production.
- Big Data Machine Learning: To apply machine learning to large-scale datasets, enabling distributed computing and faster insights.
Feel free to connect with me via:
- Email: [email protected]
- LinkedIn: de-pramit
- GitHub: Pramit726
Let's collaborate on data science or machine learning projects.