Python

A Versatile Language for Diverse Problems

My experience with Python showcases its versatility across different domains, from data-intensive machine learning tasks to building utility APIs.

Data Science & Machine Learning

Python is my primary language for data science. In projects like ODIR Classification and OLX Car Regression, I used Python's powerful data science stack—including Pandas, Scikit-learn, and TensorFlow—to process data, build predictive models, and extract insights.

API Development

I have also used Python to create functional backend services. The gmaps-reverse project is an example where I built a small, efficient API using a Python web framework to provide a specific service, demonstrating my ability to use the language for general-purpose backend development.

Key Competencies

• Core Language: Strong grasp of Python syntax, data structures, and object-oriented features.
• Data Science Stack: Pandas, NumPy, Matplotlib for data manipulation and visualization.
• Machine Learning: Scikit-learn for classical ML models, TensorFlow/Keras for deep learning.
• Web Frameworks: Experience with frameworks like Flask or FastAPI for building APIs.
• Tooling: Use of Jupyter Notebooks for analysis and pip for package management.