Hello everyone. This is going to be a tutorial on how to install tensorflow using official pre-built pip packages. To install tensorflow with pip packages is easier as compared to building using CMake or Bazel. Pre-built pip package are fully tested officially. However, since they are configured in such a way that they can support legacy hardware too, using pip package may not use full capability on your new and powerful hardware. Building pip package the solution to fully optimize tensorflow to use full capability of your hardware. However, building is a time-consuming process and generally recommended for advanced users only. If you are looking to build tensorflow instead, you can check out our other blog posts:
In this tutorial, we will look at how to install tensorflow CPU and GPU both for Ubuntu as well as Windows OS. For our purpose, we will look at installing the latest version tensorflow, tensorflow 1.5.0, at the time this blog is published. To install tensorflow in any OS, I highly recommended using virtual environment setup (conda, virtualenv etc.)
CPU version of tensorflow is recommended for new users of tensorflow. Unless you are handling large datasets, CPU version of tensorflow works just fine. Also, this is the simplest method to install tensorflow.