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Tag: MNIST

#009 TF An implementation of a Convolutional Neural Network in tf.keras – MNIST dataset

20.01.2020

In this post we will see how we can classify handwritten digits using Convolutional Neural Network implemented in TensorFlow 2.0. Required packages: Numpy Matplotlib Tensorflow Sklearn Seaborn Table of Contents: Load the digit dataset Implementing a Neural Network Visualization and Testing 1. Load the digit dataset Let start with importing all necessary libraries. After imports, we can use imported module to load mnist data. The load_data() function will automatically download and split our data into…
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#008 TF An implementation of a Convolutional Neural Network in tf.keras – MNIST dataset

02.04.2019

In this post we will see how we can classify handwritten digits using convolutional neural network implemented in Keras. Required packages: Numpy Matplotlib Keras Tensorflow Sklearn Seaborn __future__ Keras-vis Table of Contents: Load the digit dataset Implementing a Neural Network Visualization Test our model Save a model as picture Activation Maps Saliency maps Activations Now we can plot some predictions, to see how our model works. Images for testing can be downloaded from the internet…
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#008 TF 2.0 An implementation of a Shallow Neural Network in tf.keras – digits dataset

08.02.2019

In this post we will see how we can classify handwritten digits using shallow neural network implemented with tf.keras. Table of Contents: Load the digit dataset Implementing a Neural Network Visualization and Testing 1. Load the digits dataset First, let us import all necessary libraries. After imports, we can use imported module to load digits data. The load_digits() function will just download data and we need to split it into train and test sets. We can also…
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