Made the article relevant to Anaconda's ToS changes and our pivot to use Miniforge

docs/cheaha/tutorial/pytorch_tensorflow.md

@@ -1,8 +1,8 @@
-# Anaconda Environment Tutorial for PyTorch and TensorFlow
+# Conda Environment Tutorial for PyTorch and TensorFlow
 
-The below tutorial would show you steps on how to create an Anaconda environment, activate, and install libraries/packages for machine and deep learning (PyTorch and Tensorflow) using an Anaconda environment on Cheaha. There are also steps on how to access the terminal, as well as using Jupyter Notebook's Graphical User Interface (GUI) to work with these Anaconda environments. There are detailed steps here to guide your creation of a [Jupyter Notebook job.](../open_ondemand/ood_layout.md#interactive-apps)
+The below tutorial would show you steps on how to create a Conda environment, activate, and install libraries/packages for machine and deep learning (PyTorch and Tensorflow) using an Anaconda environment on Cheaha. There are also steps on how to access the terminal, as well as using Jupyter Notebook's Graphical User Interface (GUI) to work with these Anaconda environments. There are detailed steps here to guide your creation of a [Jupyter Notebook job.](../open_ondemand/ood_layout.md#interactive-apps)
 
-## Installing Anaconda Environments Using the Terminal
+## Installing Conda Environments Using the Terminal
 
 To access the terminal (shell), please do the following.
 
@@ -32,11 +32,11 @@ The instructions below, provide a recommended step by step guide to creating and
 
 ## Installing PyTorch Using the Terminal
 
-There are two instances of PyTorch that can be installed, one requiring GPUs, and another utilising only CPUs. GPUs generally improve project compute speeds and are preferred. For both instances of pytorch, please follow these steps;
+There are two instances of PyTorch that can be installed, one requiring GPUs, and another utilizing only CPUs. GPUs generally improve project compute speeds and are preferred. For both instances of pytorch, please follow these steps;
 
-1. [Create](../../workflow_solutions/using_anaconda.md#create-an-environment) and [activate](../../workflow_solutions/using_anaconda.md#activate-an-environment) an environment as stated in these links.
+1. [Create](../../workflow_solutions/using_conda.md#create-an-environment) and [activate](../../workflow_solutions/using_conda.md#activate-an-environment) an environment as stated in these links.
 
-1. Access the terminal following the steps [here](#installing-anaconda-environments-using-the-terminal).
+1. Access the terminal following the steps [here](#installing-conda-environments-using-the-terminal).
 
 <!-- markdownlint-disable MD046 -->
 !!! note
@@ -134,4 +134,4 @@ The image below shows an output that the TensorFlow library will utilize the ava
     The information (I) and warning (W) outputs notifies you of the installed Tensorflow binary and how it would function. The I output informs you that the installed Tensorflow library will utilize your CPU for additional speed when GPUs are not the most efficient way to do processing for these operations. The W output tells you TensorRT is not available, please note TensorRT is not currently supported on our systems.
 <!-- markdownlint-enable MD046 -->
 
-Now that you have completed the tutorial, you can find more Anaconda information here, [Using Anaconda page](../../workflow_solutions/using_anaconda.md#anaconda).
+Now that you have completed the tutorial, you can find more Conda information here, [Using Conda page](../../workflow_solutions/using_conda.md#conda).