This ‘TensorDash’ application lets you track and monitor deep learning model metrics

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Image Source: https://cleanpegasus.github.io/TensorDash/
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Now you can monitor your deep learning model using an application called ‘TensorDash’ remotely instead of sitting in front of your workstation to monitor your DL model’s progress. ‘TensorDash’ lets you remotely monitor your deep learning model’s metrics and notifies you when your model training is completed or crashed. This could be really helpful while training a model on the cloud (Google Colab).

Features:

  1. You can watch your model train in real-time
  2. Remotely get details on the training and validation metrics
  3. Get notified when your model has completed training or when it has crashed.
  4. Get detailed analytics on your model’s metrics.

Installation: (Source: https://github.com/CleanPegasus/TensorDash)

Install TensorDash from PyPI :

Note: These installation steps assume that you are on a Linux or Mac environment. If you are on Windows, you will need to remove sudo to run the commands below.

sudo pip install tensor-dash

If you are using a virtualenv, you may want to avoid using sudo:

pip install tensor-dash

Alternatively: install TensorDash from the GitHub source:

First, clone TensorDash using git:

git clone https://github.com/CleanPegasus/TensorDash.git

Then, cd to the TensorDash folder and run the install command:

cd TensorDash
sudo python setup.py install

Documentation: https://cleanpegasus.github.io/TensorDash/

Github: https://github.com/CleanPegasus/TensorDash

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