🗂️ Pradyun's Documentation Repository

A personal knowledge base and dev journal for documenting my projects, research, and technical learnings. This repository serves as a central archive of Jupyter notebook blogs and GitHub Issues used for tracking progress, ideas, and problem-solving across multiple domains.

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✨ Features

• 📓 Jupyter Blog Posts – Narrative-style technical writeups and walkthroughs in notebook format.
• 🔧 Project-Specific Notes – Exploratory analysis, debug notes, and design decisions for ongoing and past projects.
• 🧠 Problem-Solving Logs – GitHub Issues are used to document bugs, questions, and incremental discoveries as part of my workflow.
• 📂 Topic Coverage – Includes content from software engineering, machine learning, biotechnology, and system design.

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🚀 Getting Started

To explore the notebooks:

1. Clone the repository

   git clone https://github.com/<Prad-coder>/<PradyunCSP_>.git
   cd <PradyunCSP_>

2. Open JupyterLab or Jupyter Notebook

   jupyter lab
   # or
   jupyter notebook

3. Browse the documentation notebooks

   • Notebooks are organized by topic, project, or theme.
   • Some notebooks include interactive widgets or visualizations.

Note: Some notebooks may depend on local or project-specific data. See individual notebook headers for instructions.

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🎮 Usage

• Use this repo to trace the evolution of ideas and designs across my projects.
• Issues act as time-stamped logs for what I tried, what worked, and what didn’t.
• Jupyter notebooks document results, technical breakdowns, and analysis.

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🤝 Contributing

This is a personal repository intended primarily for my own use. That said, suggestions, corrections, and discussions via Issues are welcome if you find the content helpful or interesting.

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🧭 Issues / Roadmap

I use GitHub Issues as:

• ✍️ A scratchpad for design decisions
• 🐛 A tracker for bugs, debugging insights, and reproducibility notes
• 🔍 A searchable archive of experiments and iterations

There is no strict roadmap—this repository grows organically with each project I document.

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🙌 Acknowledgments

Thanks to the open-source and scientific computing communities for tools like:

• Jupyter
• NumPy, pandas, matplotlib, and Scikit-Learn
• GitHub Issues for structured note-taking

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🧠 Philosophy

This repo embodies a principle of working with the garage door up—documenting as I build, fail, and learn. It's a place for raw ideas, partial wins, and occasional breakthroughs.