🐍 Python Learning Repository

Welcome to my Python Learning Repository — a collection of personal learning notes, coding exercises, and project prototypes created while studying Python and its related frameworks.

This repository serves as both a record of progress and a reference hub for topics across data analysis, web development, and AI engineering.

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📘 Purpose

The goal of this repository is to: • Document my continuous learning process in Python programming • Share reproducible code snippets, notebooks, and mini-projects • Provide reference implementations for topics such as: • Data handling and visualization • API and web application development • Machine learning and AI frameworks

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🧩 Repository Structure

Python_Learning_Repository/ │ ├── basics/ # Python syntax, data types, and control structures ├── web_development/ # FastAPI, Streamlit, Flask, and REST API examples ├── data_science/ # Pandas, NumPy, scikit-learn, and visualization notebooks ├── ai_llm/ # LLM-based projects (LangChain, OpenAI API, etc.) ├── automation/ # Scripts for workflow automation ├── notes/ # Study notes and markdown summaries └── README.md # This file

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🚀 Topics Covered • Python Fundamentals: Syntax, data types, and OOP • Web Development: FastAPI, Streamlit, and backend fundamentals • Data Science: Data cleaning, analysis, and visualization • Machine Learning: Model training with scikit-learn • LLM / AI Engineering: Building tools with LangChain and OpenAI API • Cloud & Deployment: Deta Space, AWS Lambda, and CI/CD basics

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🛠️ Tools & Environment • Language: Python 3.10+ • Editor: VS Code / Jupyter Notebook / Google Colab • Libraries: FastAPI, Streamlit, LangChain, Pandas, NumPy, scikit-learn • Deployment: Deta Space, AWS Lambda, Render (for experimentation)

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📚 Learning Philosophy

I believe in learning by building — every notebook or script in this repository reflects something I’ve implemented to understand how it truly works. Mistakes, iterations, and insights are all part of the process.

If any of these examples help your learning too, feel free to fork, star ⭐, or share feedback.

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🤝 Contributions

This is primarily a personal learning log, but constructive suggestions and pull requests are always welcome.

If you’d like to discuss or share your own learning journey, feel free to open an Issue or connect with me on GitHub.

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🧠 License

This repository is open under the MIT License — you are free to use, modify, and share the content with proper attribution.