# Prasad Raju G

> This is a machine-readable summary of iamprasadraju.github.io for LLM crawlers.

## About
Prasad Raju G is an independent AI researcher focusing on ML/DL algorithms, Python, PyTorch, reproducing arXiv research papers, and building systems engineering projects on GitHub. His work sits at the intersection of applied mathematics, deep learning, and systems engineering.

## Skills
Python, C++, C, Applied Mathematics, Machine Learning, Deep Learning, System Design, Performance Engineering, Computer Vision.

## Interests
Artificial Intelligence, Game Theory, Quantum Physics, Neuroscience, Bioinformatics, Cryptography, Robotics, Quant Finance.

## Projects

- [Tic Tac Toe](https://iamprasadraju.github.io/projects/2026-04-16-Tic-Tic-Toe.html): A graphical, pixel-art style Tic-Tac-Toe game built with Python and Pygame. It features classic two-player action with automated win detection and particle effects.
- [Gen-CLI](https://iamprasadraju.github.io/projects/2026-05-08-gen-cli.html): Gen-CLI is a powerful Python-based command-line tool designed for rapidly generating boilerplate code and framework templates. It streamlines developer workflows by scaffolding projects across multiple programming languages instantly.
- [TrueML](https://iamprasadraju.github.io/projects/2026-06-08-TrueML.html): A zero-abstraction machine learning framework designed for deep understanding of training loops, gradients, and model architecture. TrueML exposes the fundamental primitive operations of ML, enabling developers and researchers to explicitly invoke every step without black-box methods.
- [AlgoX](https://iamprasadraju.github.io/projects/2026-06-08-algoX.html): AlgoX is a high-performance Python library that introduces STL-style data structures and algorithms via a native C backend. It is optimized for speed, learning, and algorithmic experimentation.

## Notes & Articles

- [Working With ESP32](https://iamprasadraju.github.io/notes/2025-08-21-working-with-esp32.html): A comprehensive guide on working with the ESP32 microcontroller, including hardware specs, software tools like ESP-IDF, and programming with MicroPython and C++.
- [Sorting](https://iamprasadraju.github.io/notes/2025-12-08-sorting.html): A comprehensive guide to sorting algorithms, including Selection Sort, Bubble Sort, and Insertion Sort, covering their mechanics, complexities, and use cases.
- [In-built Datastructures in Python, C++, C](https://iamprasadraju.github.io/notes/2026-03-08-in-built-datastructures.html): A comprehensive guide and quick reference for in-built data structures in Python, C++, and C. Discover time complexities, common operations, and interview questions.
- [Mac Setup](https://iamprasadraju.github.io/notes/2026-04-11-Mac-Setup.html): A comprehensive guide to setting up a new Mac for development. Includes step-by-step instructions for installing CLI tools, essential software, programming languages, and Python libraries.
- [Learning Stats](https://iamprasadraju.github.io/notes/2026-04-14-Learning-Stats.html): A curated collection of top resources, including Harvard and MIT courses, and foundational textbooks for mastering statistics and probability in Python.
- [Git Guide](https://iamprasadraju.github.io/notes/2026-04-16-Git-Guide.html): A comprehensive guide on Git best practices, including branch naming conventions and how to write clear, effective commit messages.
- [Stats 110](https://iamprasadraju.github.io/notes/2026-04-17-Stats-110.html): Comprehensive notes for the Harvard Stats 110 course, exploring the logic of uncertainty and probability. Discover the fundamental differences between mathematics and statistics.
- [Book - Mathematics for Machine learning](https://iamprasadraju.github.io/notes/2026-05-02-maths-for-ml-book.html): Explore the core mathematical concepts behind Machine Learning, covering linear algebra, calculus, probability, and optimization techniques for AI models.

## Links & Entities
- [Website](https://iamprasadraju.github.io/)
- [GitHub](https://github.com/iamprasadraju)
- [Hugging Face](https://huggingface.co/iamprasadraju)
- [Google Scholar](https://scholar.google.com/citations?hl=en&user=n_0swYgAAAAJ)
- [Kaggle](https://www.kaggle.com/iamprasadraju)
- [LinkedIn](https://linkedin.com/in/realprasadraju)
- [Email](mailto:gls.prasadraju@gmail.com)
- [Research Papers](https://iamprasadraju.github.io/ResearchRack/)
- [Books](https://iamprasadraju.github.io/ResearchRack/books)

## RSS Feeds
- [Master Timeline](https://iamprasadraju.github.io/feed.xml)
- [Notes](https://iamprasadraju.github.io/feed/notes.xml)
- [Projects](https://iamprasadraju.github.io/feed/projects.xml)