Removed image for copyright reasons

Author: madeline-underwood

content/learning-paths/embedded-and-microcontrollers/training-inference-pytorch/_index.md

@@ -1,5 +1,5 @@
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-title: "Edge AI on Arm with PyTorch and ExecuTorch: Tiny Rock, Paper, Scissors"
+title: "Edge AI on Arm: PyTorch and ExecuTorch Rock Paper Scissors"
 
 minutes_to_complete: 60
 

content/learning-paths/embedded-and-microcontrollers/training-inference-pytorch/env-setup-1.md

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-title: Environment Setup
+title: Set up your environment 
 weight: 2
 
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-## Environment setup for Tiny Rock, Paper, Scissors on Arm (PyTorch + ExecuTorch)
+## Set up your environment for Tiny Rock, Paper, Scissors on Arm (PyTorch + ExecuTorch)
 
 
 
@@ -19,11 +19,6 @@ A Convolutional Neural Network (CNN) is a type of deep neural network primarily
 
 A convolutional neural network (CNN) is a deep neural network designed to analyze visual data using the *convolution* operation. CNNs learn spatial hierarchies of features - from edges and textures to shapes and objects - directly from pixels.
 
-![Conceptual diagram of a convolutional neural network alt-text#center](image.png "Conceptual CNN diagram")
-
-Image credits: [Medium article](https://medium.com/@atul_86537/learning-ml-from-first-principles-c-linux-the-rick-and-morty-way-convolutional-neural-c76c3df511f4)
-
-
 Common CNN applications include:
 
 - Image classification: identify the main object in an image, such as classifying a photo as a cat or dog