Neural Networks in Python: Difference between revisions
(Created page with "=Before You Begin= We've been using the Keras API with the TensorFlow backend for our simulations. Our code often also uses the numPy and SciKit libraries because I often stea...") |
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We've been using the Keras API with the TensorFlow backend for our simulations. Our code often also uses the numPy and SciKit libraries because I often steal code examples that happen to have been coded using those libraries. When you get started, you will want to make sure that all the requisite libraries are installed. Pip (the Python package installer) has a function called <code>freeze</code> that will list all your installed libraries. This list can be dumped to a text file and used to share the list of Python packages you'll need to run any of the code we've developed: | We've been using the Keras API with the TensorFlow backend for our simulations. Our code often also uses the numPy and SciKit libraries because I often steal code examples that happen to have been coded using those libraries. When you get started, you will want to make sure that all the requisite libraries are installed. Pip (the Python package installer) has a function called <code>freeze</code> that will list all your installed libraries. This list can be dumped to a text file and used to share the list of Python packages you'll need to run any of the code we've developed: | ||
pip freeze > requirements.txt | pip freeze > requirements.txt | ||
Now any lab member can use ''' | Now any lab member can use '''requirements.txt''' to ensure they have the requisite Python packages installed: | ||
pip install -r requirements.txt | pip install -r requirements.txt | ||
I've got the current list of dependencies on ubfs/Scripts/Python/requirements.txt | I've got the current list of dependencies on ubfs/Scripts/Python/requirements.txt | ||
Revision as of 11:39, 8 March 2019
Before You Begin
We've been using the Keras API with the TensorFlow backend for our simulations. Our code often also uses the numPy and SciKit libraries because I often steal code examples that happen to have been coded using those libraries. When you get started, you will want to make sure that all the requisite libraries are installed. Pip (the Python package installer) has a function called freeze that will list all your installed libraries. This list can be dumped to a text file and used to share the list of Python packages you'll need to run any of the code we've developed:
pip freeze > requirements.txt
Now any lab member can use requirements.txt to ensure they have the requisite Python packages installed:
pip install -r requirements.txt
I've got the current list of dependencies on ubfs/Scripts/Python/requirements.txt