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 tensorflow.org 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 python.org. 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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