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.

Introduction to Neural Nets:    • Introduction to Neural Networks in Py...  
Link to my code (github): https://github.com/KeithGalli/neural-...
Link to Google Colab file: https://colab.research.google.com/dri...

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Resources!

Learn more about CNNs
Good written overview: https://towardsdatascience.com/a-comp...
Good video overview (@CodeEmporium ):    • Convolution Neural Networks - EXPLAINED  
Illustrated Examples of CNNs: https://towardsdatascience.com/illust...
MNIST Example: https://keras.io/examples/mnist_cnn/

Learn more about TensorFlow datasets
https://www.tensorflow.org/datasets/o...
https://www.tensorflow.org/datasets/c...

Learn more about Kerastuner
Documentation: https://keras-team.github.io/keras-tu...
@sentdex :    • Optimizing Neural Network Structures ...  
@krishnaik06 :    • Tutorial 27- Create CNN Model and Opt...  

Practice your Python Pandas data science skills with problems on StrataScratch!
https://stratascratch.com/?via=keith

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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

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If you are curious to learn how I make my tutorials, check out this video:    • How to Make a High Quality Tutorial V...  

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