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How to Install Python Tensorflow in Windows?

  • Last Updated : 21 Apr, 2020

Tensorflow is a free and open-source software library used to do computational mathematics to build machine learning models more profoundly deep learning models.
It is a product of Google built by Google’s brain team, hence it provides a vast range of operations performance with ease that is compatible with human behavior for ML and DL. It can run on multiple CPUs and GPUs.

Features of Tensorflow:

  • Computational Framework – It is a platform that provides huge computational framework at one place. In this, computation is approached as a dataflow graph.
  • Mobile Deployment – It is an easy way to build projects with mobile deployment
  • High Performance – Due to its ease and varying toolkits, it gives high-performance user experience.

Downloading and Installation:

Tensorflow can be downloaded from its official Website and can be installed with the help of following steps:
Step 1: Click on Install on top navigation bar of Tensorflow website.

Step 2: Before proceeding we need to get python environment. Choose pip in the left side and go to python section and install python environment to work on it.

Step 3: Python environment can be downloaded from To install python on windows refer to: How to install Python on Windows?
Step 4: To install Tensorflow, we need pip for python. Usually, pip comes already installed if the python version is 3 or above. To know more about pip installation please refer: How to install pip in Windows?

For all OS users check the pip section of TensorFlow as shown in the following screenshot:

Tensorflow can also be downloaded for installation on different OS:

Step 5: Creating a Tensorflow virtual environment

This can be done with the use of following command:

pip install --user virtualenv

Step 6: After setting up the virtual environment, use the following command to install Tensorflow pip package:

pip install --upgrade tensorflow 


Once installed you can import TensorFlow in your python programming environment as you choose(here python IDE as stated in step 5).

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