TensorBoard: Visualizing Machine Learning Experiments

TensorBoard is an open-source tool developed by Google for visualizing machine learning experiments, especially those built with TensorFlow. It provides a suite of web-based utilities to help developers understand, debug, and optimize their models.

Key Features

• 📊 Real-time Metrics Monitoring: Track loss, accuracy, and other metrics during training.
• 📈 Graph Visualization: Explore computational graphs and model architecture.
• 📝 Log Analysis: Inspect training logs, histograms, and distributions.
• 🧠 TensorBoard Plugins: Extend functionality with tools like Scalars, Images, and Histograms.

How to Use

1. Install TensorBoard:

   pip install tensorboard  
   

2. Start TensorBoard:

   tensorboard --logdir=path/to/logs  
   

3. Access Dashboard: Open http://localhost:6006 in your browser.

Resources

• 📘 TensorFlow官方文档 for advanced usage.
• 🧩 Explore TensorBoard plugins to enhance your workflow.