This package is for storing machine learning models with meta data in Rust so they can be used on the SurrealDB server.
SurrealML is a feature that allows you to store trained machine learning models in a special format called 'surml'. This enables you to run these models in either Python or Rust, and even upload them to a SurrealDB node to run the models on the server
- A basic understanding of Machine Learning: You should be familiar with ML concepts, algorithms, and model training processes.
- Knowledge of Python: Proficiency in Python is necessary as SurrealML involves working with Python-based ML models.
- Familiarity with SurrealDB: Basic knowledge of how SurrealDB operates is required since SurrealML integrates directly with it.
- Python Environment Setup: A Python environment with necessary libraries installed, including SurrealML, PyTorch or SKLearn (depending on your model preference).
- SurrealDB Installation: Ensure you have SurrealDB installed and running on your machine or server
We have removed PyO3 for a raw dynamic C lib written in rust. This is how working with Python and we can also link this dynamic C lib to other languages such as JavaScript. The new Python client is housed in the clients
directory. Please visit this for the updated installation and API docs.