Model Tracking and Monitoring
When training deep learning models, it is crucial to take various factors into account during the training process. This approach enables us to conduct highly effective experiments. In this chapter, we will cover experiment tracking through sophisticated tools. We will learn how to track experiments by logging and then monitoring them with TensorBoard and Weights & Biases (W&B). These tools enable us to efficiently host and track experimental data such as loss, or other metrics that help us to optimize model training.
In this chapter, we will cover the following topic:
- Tracking model metrics
- Tracking model training with TensorBoard
- Tracking model training live with W&B
