Train a TensorFlow model locally

In this quickstart, we will run a TensorFlow model with the MNIST dataset locally in AI Tools. The MNIST database has a training set of 60,000 examples, and a test set of 10,000 examples of handwritten digits.

Prerequisites

Before you begin, ensure you have the following installed:

Google TensorFlow

Run the following command in a terminal.

pip install tensorflow

or if you have an Nvidia GPU

pip install tensorflow-gpu

NumPy and SciPy

run the following command in a terminal:

pip install numpy scipy

Download sample code

Download this GitHub repository containing samples for getting started with deep learning across TensorFlow, CNTK, Theano and more.

Open solution and train model

• Launch Visual Studio and select File > Open > Project/Solution.

• Select the examples\tensorflow subfolder from the samples repository dowloaded and open the TensorflowExamples.sln file.

• Find the MNIST Project in the Solution Explorer, right click and select Set as StartUp Project.

• Click Start.

• The output will be printed in the console.

Train a TensorFlow model in the cloud