Difference between revisions of "TensorBoard"
m |
m |
||
| Line 8: | Line 8: | ||
[http://www.google.com/search?q=tensorboard+deep+machine+learning+ML ...Google search] | [http://www.google.com/search?q=tensorboard+deep+machine+learning+ML ...Google search] | ||
| − | * [http://www.tensorflow.org/tensorboard TensorBoard | + | * [http://www.tensorflow.org/tensorboard TensorBoard] | [[Google]] ...TensorFlow's visualization toolkit |
* [[TensorFlow]] | * [[TensorFlow]] | ||
* [[TensorFlow Playground]] | * [[TensorFlow Playground]] | ||
Revision as of 13:01, 22 August 2020
YouTube search... ...Google search
- TensorBoard | Google ...TensorFlow's visualization toolkit
- TensorFlow
- TensorFlow Playground
- TensorBoard: Graph Visualization
- Neural Networks Playground
- Visualization
- Colaboratory (Colab)
- Data Flow Graph (DFG)
- TensorWatch
- Principal Component Analysis (PCA) ...linear
- T-Distributed Stochastic Neighbor Embedding (t-SNE) ...non-linear
- Graphical Tools for Modeling AI Components
In machine learning, to improve something you often need to be able to measure it. TensorBoard is a tool for providing the measurements and visualizations needed during the machine learning workflow. It enables tracking experiment metrics like loss and accuracy, visualizing the model graph, projecting embeddings to a lower dimensional space, and much more. provides the visualization and tooling needed for machine learning experimentation:
- Tracking and visualizing metrics such as loss and accuracy
- Visualizing the model graph (ops and layers)
- Viewing histograms of weights, biases, or other tensors as they change over time
- Projecting embeddings to a lower dimensional space
- Displaying images, text, and audio data
- Profiling TensorFlow programs
