Race Modelling

The GRV Greyhound Racing Model represents a personal project in deep machine learning, aimed at predicting the outcomes of races across Australia and New Zealand. Tailoring a custom Gated Recurrent Unit model to navigate the complexities of non-uniform time series data in greyhound racing, the project serves as a prime example of innovative problem-solving and application of advanced machine learning techniques.

• Developed a deep learning model for predicting race outcomes.
• Automated real-time data updates via integrated API feeds.
• Engineered a novel solution using custom GRU for time series analysis.
• Deployed a live dashboard for remote monitoring of model training.