How to install Tensorflow and CUDA in linux systems - a beginners Guide

series: "Linux & Developer Tools" --- part: 1 --- chapter: "1" --- description: "Step-by-step guide to installing Nvidia drivers, CUDA, cuDNN, and TensorFlow on Linux — get your GPU-accelerated ML environment running correctly." --- Getting GPU working for tensorflow and CUDA is a difficult task for naive linux users. In this guide, you can easily understand the installation process. This guide is focussed on debian based distros, but it can be used on any linux distro with respective command for the task according to distro. So, What do we need for working tensorflow and nvidia drivers on linux > - A linux Machine, ofcourse. > - Nvidia Drivers Installed. > - Compatible tensorflow version Installed > - Tensorflow compatible Cuda Version Installed. 1. Make sure You have nvidia Drivers installed
I have nvidia geforce 940mx, So the latest drivers for me was v430.14
You can download and install Latest drivers from [here](https://www.nvidia.in/Download/index.aspx?lang=en-in) 2. Reboot and make sure nvidia drivers are installed successfully
- run `nvidia-smi` in terminal
It should give some output in tabular form like here : [](https://i.imgur.com/blHMfTv.png) - make sure Nouveau drivers are disbaled ( These are automatically disabled after nvidia drivers installation)
to check: run `lsmod | grep nouveau` in terminal * If there is no output