TensorBoard
TensorBoard is a web-based visualization toolkit developed by TensorFlow for tracking and visualizing machine learning experiments. It provides interactive dashboards to monitor metrics like loss and accuracy, visualize model architectures, and analyze training data distributions. It is widely used for debugging, optimizing, and understanding deep learning models during development.
Developers should use TensorBoard when training machine learning models, especially with TensorFlow or PyTorch (via integrations), to gain insights into model performance and behavior. It is essential for hyperparameter tuning, detecting overfitting, and comparing multiple experiments, making it crucial for research, production model development, and educational purposes in AI/ML workflows.