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Kikumu/README.md

💫 About Me:

🔭 I’m currently working on: Developing a Retrieval Augmented Generation (RAG) model using Langchain, Huggingface and Ollama with advanced techniques to improve contextual relevance and interaction.

🌱 I’m currently learning: ML model pipeline automation, Data pipeline automation, Containerisation

💬 Ask me about: Machine learning model deployment, reinforcement learning techniques, or how AI can improve flood prediction and music recommendation systems.

⚡ Fun fact: I like spicy noodles

🌐 Socials:

LinkedIn

💻 Tech Stack:

C# AWS Lua Python Windows Terminal Anaconda nVIDIA Django FastAPI Flask OpenCV MusicBrainz MicrosoftSQLServer MySQL SQLite Keras Matplotlib NumPy Pandas PyTorch scikit-learn Scipy TensorFlow GitHub Git GitHub Actions Confluence Jira Notion Raspberry Pi Postman Plex nVIDIA

📊 GitHub Stats:




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  1. DCGAN-with-facedata DCGAN-with-facedata Public

    This repository Investigates DCGAN using facedata. Serves as a personal cautionary tale when working with GANS.

    Jupyter Notebook

  2. Reinforcement-Learning-repo Reinforcement-Learning-repo Public

    A repo where I look into the details and practice on how to properly utilize reinforcement learning

    Jupyter Notebook

  3. Contra-Lua Contra-Lua Public

    Genetic algorithm implemented using lua and bizhawk to play classic contra retro game

    Lua

  4. Flood-algo-draft Flood-algo-draft Public

    flood algo test suite(Prototyping using CNN-RNN)

    Jupyter Notebook

  5. LBCGAN LBCGAN Public

    Location based conditional gan - this is only for prototype purposes

    Jupyter Notebook