TensorFlow is Google’s Open Source Machine Learning Framework for dataflow programming across a range of tasks. Nodes in the graph represent mathematical operations, while the graph edges represent the multi-dimensional data arrays (tensors) communicated between them.
Tensors are just multidimensional arrays, an extension of 2-dimensional tables to data with a higher dimension. There are many features of TensorFlow which makes it appropriate for Deep Learning.
Airbnb: It improves the guest experience by using TensorFlow to classify images and detect objects at scale.
CocaCola: The advancements in Tensorflow enabled Coco-Cola to finally achieve a long-sought frictionless proof-of-purchase capability.
GE Healthcare: GE trained a Neural Network using TensorFlow to identify specific anatomy during brain MRIs to help improve speed and reliability.
Twitter: Twitter used TensorFlow to build their “Ranked Timeline”, allowing users to not miss any tweets even if they follow a thousand other users.
To install TensorFlow, it is important to have “Python” installed in your system. Python version 3.4+ is considered the best to start with TensorFlow installation.
Consider the following steps to install TensorFlow in Windows operating system.
Step 1 − Verify the python version being installed
Step 2 − A user can pick up any mechanism to install TensorFlow in the system. We recommend “pip” and “Anaconda”. Pip is a command used for executing and installing modules in Python.
Before we install TensorFlow, we need to install Anaconda framework in our system.
After successful installation, check in command prompt through “conda” command. The execution of command is displayed below −
Step 3 − Execute the following command to initialize the installation of TensorFlow −
conda create -n tensorflow_env tensorflow |
It downloads the necessary packages needed for TensorFlow setup.
Step 4 − After successful environmental setup, it is important to activate TensorFlow module.
conda activate tensorflow_env
Step 5 − Use pip to install “Tensorflow” in the system. The command used for installation is mentioned as below −
pip install tensorflow |
and
pip install tensorflow-gpu |
After successful installation, it is important to know the sample program execution of TensorFlow.
Following example helps us understand the basic program creation “Hello World” in TensorFlow.
The code for first program implementation is mentioned below −
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>> activate tensorflow >> python (activating python shell) >> import tensorflow as tf >> hello = tf.constant(‘Hello, Tensorflow!’) >> sess = tf.Session() >> print(sess.run(hello)) |