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@AIYathra

AI Yathra

AI Yathra — documenting the daily journey through artificial intelligence, from code to creativity.
  • Belgium

AI Yathra 🧭

Documenting a daily journey through artificial intelligence — from first principles to deployed systems.

Hi, I'm Srimal Priyanga Fonseka — a software engineer (8+ years) now building toward an AI / Machine Learning Engineer career. AI Yathra ("yathra" = journey) is where I learn in public: each project is a checkpoint, built from the ground up rather than copied, so the reasoning is visible alongside the code.

📍 Belgium · open to relocation across the EU 🔗 LinkedIn · ✉️ hsrprf@gmail.com


🚀 Featured Projects

Project What it demonstrates Stack
Agentic Tool-Calling Demo LLM-driven function calling, dynamic tool discovery, safe parameter parsing, and Python tool execution — a clean foundation for agentic workflows. Python, LLM APIs
Pandas House-Price Pipeline End-to-end ML data pipeline: cleaning, EDA, feature engineering, and a baseline regression model on the Kaggle House Prices dataset. Python, Pandas, scikit-learn
XOR Neural Network A multi-layer perceptron solving the classic non-linear XOR problem — built to show why hidden layers and non-linear activations matter. Python, NumPy, Jupyter
Simple Brain (Perceptron from scratch) Frank Rosenblatt's 1958 Perceptron implemented from scratch — the biological and mathematical roots of learning, via a "Pizza Detector". Python

🔭 Where this is heading: the next checkpoints in the journey move from foundations to a deployed end-to-end project (model + API + live demo on Hugging Face / Streamlit).


🛠️ Tech Stack

Languages: Python · SQL · JavaScript ML / AI: scikit-learn, neural networks (from scratch + frameworks), LLM tool-calling / agents Data: Pandas, NumPy, EDA, feature engineering Engineering foundation: software development lifecycle, system design, DevOps practices, REST APIs


👤 Background

Before AI, I spent years shipping web, mobile, and cloud software — as a software engineer, a startup co-founder, and a technology consultant for SMEs. That foundation in building and delivering real systems is what I'm now applying to machine learning.

📄 Full CV available on request · 💬 Best reached via LinkedIn

Popular repositories Loading

  1. ai365-simple_brain ai365-simple_brain Public

    A scratch-built Python implementation of Frank Rosenblatt's 1958 "Perceptron," demonstrating the biological roots of AI learning through a simple "Pizza Detector" example.

    Python

  2. ai365-xor_problem_neural_network ai365-xor_problem_neural_network Public

    This repository explores the classic XOR problem — a foundational challenge in neural network history — and demonstrates how a simple multi-layer perceptron (MLP) can solve it using non-linear acti…

    Jupyter Notebook

  3. ai365-agentic_tool_calling_dapp ai365-agentic_tool_calling_dapp Public

    A minimal, educational agentic demo showcasing dynamic tool discovery, LLM‑driven function calling, safe parameter parsing, and Python tool execution. Designed as a clean foundation for understandi…

    Python

  4. ai365-pandas_houseprice_pipeline ai365-pandas_houseprice_pipeline Public

    A clean, modular data pipeline using Pandas to transform the Kaggle House Prices dataset into an AI‑ready, ML‑ready format. Includes data cleaning, EDA, feature engineering, and a baseline regressi…

    Python

  5. .github .github Public

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