In this video we walk through the process of training a convolutional neural net to classify images of rock, paper, & scissors. We do this using the Tensorflow & Keras libraries. This is a follow-up to the first video I posted on neural networks.

Video Timeline!
0:00​ Video Overview
0:33​ Getting Started (Setup & Installation)
2:24​ Finding datasets to use
6:02​ Data Preparation
10:26​ Additional Data Prep (Convert data to NumPy format)
15:22​ Reshape Data & Normalize values between 0-1
19:39​ Train our first network to classify images
25:06​ Convolutional Neural Net (CNN) approach
28:48​ Using GPU on Google Colab (speed up training)
31:22​ Improving our CNN (reduce image size, max pooling, dropout, etc)
40:18​ Using Kerastuner to automatically pick best hyperparameters
52:50​ Save & Load our models
54:16​ Plot NumPy arrays as images
57:38​ Convert JPG/PNG images to NumPy
1:00:20​ Final thoughts

Link to my code (github): https://github.com/KeithGalli/neural-nets
Link to Google Colab file: https://bit.ly/2MQ4rji

Subscribe: https://www.youtube.com/channel/UCq6XkhO5SZ66N04IcPbqNcw

#python #tensorflow