Build a Basic Neural Network In 15 Minutes - MalkamDior

https://drive.google.com/uc?export=view&id=1Cf8OVMcMoKtNPSbPE74VoCw5UnYVp9Pv

Build a basic Neural Network In 15 Minutes to classify clothing items using Keras & Tensorflow.

Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes. 
We intend Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing splits.


Here's an example how the data looks (each class takes three-rows):


https://drive.google.com/uc?export=view&id=1ZVX9VqCvAcEGA77O8jWbFIExreph3ICMhttps://drive.google.com/uc?export=view&id=1Pmhwi3cBgTyaA6dTWpC4kbEKpnmb7arP


In this video we build a very basic Deep Neural Network which categorises items of clothing. 


I try to simplify the process as much as possible. I used Python along with TensorFlow and Keras to build this neural network. The dataset used to train the model is the Fashion-MNIST dataset.




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