I'm a Data Scientist and Full-Stack Developer specializing in building robust, production-ready applications that merge machine learning with modern web development. My work focuses on creating pragmatic, maintainable, and scalable solutions that solve real-world problems.

• Machine Learning & Data Science: PyTorch, TensorFlow, scikit-learn, Hugging Face, OpenCV, Pandas, NumPy, spaCy. My focus is on predictive analytics, NLP, and computer vision prototypes.
• Full-Stack & APIs: React, Next.js, FastAPI, Django, Flask, Node.js, RESTful APIs, GraphQL. I build end-to-end dashboards and user interfaces that bring ML models to life.
• Data Engineering: SQL (Postgres), MongoDB, Kafka, Apache Spark, Airflow. I design and manage data pipelines for effective model training and deployment.
• DevOps & Deployment: Docker, AWS, CI/CD, basic Kubernetes, Git. I ensure code is not just functional but also reproducible and scalable in production environments.

• Reproducibility: I believe that a good experiment is a reproducible one. I use notebooks and scripts to ensure that every result can be verified and built upon.
• Incremental Delivery: I favor an agile workflow: start with a functional prototype, get feedback, and then iterate toward a polished, production-ready application.
• Clear Communication: I document my work thoroughly and provide clear instructions for demos and deployments, making collaboration seamless.

• Portfolio & Open-Source: Explore my featured projects and contributions on GitHub: https://github.com/hemilkaklotar
• Professional Profile: Connect with me on LinkedIn to see my professional experience and testimonials: https://linkedin.com/in/hemil-kaklotar-018460140

I'm always open to new challenges and collaborations. Feel free to reach out if you're building a team or have an interesting project in mind.