In this tutorial, we will:

  1. Explore the MNIST and Fashion MNIST dataset like what it looks like, what are the features available and what we need to predict.

  2. Implement a Simple Linear Classifier using Tensorflow and see how well the classifier performs on these datasets using the decrease in the Cost/Loss Function depicted using a plot w.r.t Epochs and other metrics.

  3. Implement a DNNClassifier using Tensorflow Estimator API and see how easy it is to implement a classifier using Tensorflow Estimator API.

Requirements

  1. OS: Ubuntu/AWS Cloud/Google Cloud/Windows
  2. Python 3+
  3. Tensorflow
  4. Numpy [+ mkl for Windows]

Just show me the Code !!

The code for this tutorial is available as a iPython notebook here.

So, let's get started.

So, we see from this tutorial that a very simple DNN classifier with just two layers is able to reach an accuracy of 89%.

So, we have reached the end of this tutorial. I hope I was able to make you understand that how we can use Tensorflow and the Estimator API for a Classification task.

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Please feel free to leave any comments, suggestions, corrections if any :)

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