Google TensorFlow is a powerful open-source software framework used to power AI projects around the globe. TensorFlow is used for machine learning and the creation of neural networks. These make it possible for computers to perform increasingly complex tasks, such as image recognition and text analysis. When it comes to AI, most people think of powerful supercomputers crunching billions of numbers in giant databanks. But there are two parts to machine learning. There is a train/test part, where you use a lot of data to build a model. And there’s deployment, where you take a model and use it as part of a project. And that’s where the Raspberry Pi fits in. Although Raspberry Pi isn’t officially supported by Google, there are example models included for the Raspberry Pi and it can be fun to get TensorFlow up and running on a Pi. And there are lots of interesting community projects around that put TensorFlow to good use. Using TensorFlow can give you a good understanding of how AI works, and how to put AI to practical use in your projects.
To install tensorflow on Raspberry, open the terminal window and enter each line one by one and press enter after copying the installation instruction.
# Installation Instruction sudo apt install libatlas-base-dev pip3 install tensorflow
Write Hello World in TensorFlow
# Hello world with tensorflow on Raspberry pi import tensorflow as tf hello = tf.constant('Hello, TensorFlow!') sess = tf.Session() print(sess.run(hello))
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