Projects

  • Sep 2024 - Ongoing

    C++ Neural Network (from scratch)

    github.com/madmax755/Cpp-NN-from-scratch

    • Developed a MLP neural network framework in C++ from scratch, implementing core components such as backpropagation, multiple optimization algorithms (SGD, Nesterov momentum, Adam, AdamW), and activation functions (ReLU, sigmoid, softmax).

    • Implemented an efficient multi-threaded training framework to optimise batch gradient calculations, achieving a 78% speedup in training to reach 90% accuracy on a large-scale handwritten digit classification dataset.

    • Developed a Gated Recurrent Unit neural network framework in C++ from scratch, fully implementing backpropagation through time, multiple optimization algorithms (SGD, Momentum, Adam, AdamW) for efficient training, and currently working on evaluating performance for stock price prediction tasks.

  • Sep 2024 - Ongoing

    Stock Price Predictor

    github.com/madmax755/stock-price-prediction-model

    • Engineered a comprehensive quantitative stock prediction model, processing 5+ years of daily price data for multiple stocks using Python, pandas, and scikit-learn.

    • Incorporated technical indicators (e.g., MACD, RSI, Bollinger Bands) and macroeconomic factors to capture complex market dynamics.

    • Applied statistical methods including VIF analysis and regularization techniques (Ridge, Lasso) to mitigate multicollinearity and prevent overfitting, redusing MSE by 41% over baseline models.

  • Aug 2024 - Ongoing

    Self-hosted Web Server

    maxkendall.com

    • Created portfolio, minesweeper, and personal todo-list websites, self-hosted on a Raspberry Pi Zero W using Nginx as a reverse proxy and the cloudflare API to handle dynamic DNS allocation.

    • Used HTML, JavaScript, and CSS to create responsive, mobile-friendly user interfaces.