TF-MELT (TensorFlow Machine Learning Toolbox) is a collection of architectures, processing, and utilities that are transferable over a range of ML applications.
A toolbox for researchers to use for machine learning applications in the TensorFlow language. The goal of this software is to enable fast start-up of machine learning tasks and to provide a reliable and flexible framework for development and deployment. The toolbox contains generalized methods for every aspect of the machine learning workflow while simultaneously providing routines that can be tailored to specific application spaces.
First, create a new conda environment and activate:
conda create -n tf-melt python=3.11
conda activate tf-melt
Finally, install the tfmelt as a package through pip either through a local install from a git clone
If you cloned the repo and would like to install from the local git repo, navigate to the head directory where setup.py is located and type:
pip install .
If you want to update the pip install to make sure dependencies are current:
pip install --upgrade .
To install the tfmelt package directly from github simply type:
pip install git+https://github.com/NREL/tf-melt.git
If you want to run the example notebooks, they require a couple additional packages which can all be pip installed:
scikit-learnipykernelmatplotlib
pip install black isort flake8
