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MLXP vs TensorBoard

MLXP

inria-thoth.github.io

TensorBoard

tensorflow.org

Side by side

FigureMLXPTensorBoard
Price from—Free
Free plan—Yes
Free trial——
Open source——
Web—Yes
Windows—Yes
macOS—Yes
Linux—Yes
API—Yes
Self-hosted—Yes
Plans published01
Spec score · Experiment Tracking6.6 (#17)7.6 (#7)
Spec score · ML Experiment Tracking Software6.5 (#32)7.6 (#16)
LicenseThe project says MLXP is distributed under the MIT license.The TensorBoard GitHub repository identifies its license as Apache-2.0.
PurposeMLXP is an open-source Python framework for managing experiments from launching and logging through querying results.TensorBoard is a suite of visualization tools for understanding, debugging, and optimizing TensorFlow programs during machine learning experimentation.

Plans

MLXP

No plans published.

MLXP pricing →

TensorBoard

  • TensorBoardFree

TensorBoard pricing →

In their own words

MLXP

MLXP has no write-up on Specifiction yet; its figures are above.

Visit inria-thoth.github.io

TensorBoard

TensorBoard is a free suite of visualization tools for understanding, debugging and optimizing TensorFlow programs during machine-learning experiments. It tracks metrics such as loss and accuracy, and its Graph Explorer displays model graphs for inspection. Dashboards show changes in tensor distributions through histograms and percentile summaries. The tools can also display logged images, audio and text, project high-dimensional embeddings and profile TensorFlow programs. In Keras workflows, a TensorFlow callback records metrics, training graph visualizations, weight histograms and sampled profiling data. TensorBoard can be launched from the command line or in notebooks using the `%tensorboard` line magic. It is designed for offline use, including local environments, corporate firewalls and datacenters. Version 2.0 and later defaults to `--host localhost`; `--bind_all` serves it on the public network over IPv4 and IPv6. Without a TensorFlow installation, it does not support log directories on Google Cloud Storage. The README identifies Chrome and Firefox as supported browsers and warns that others may have bugs or performance issues.

Visit tensorflow.org