Introduction to Tensor Flow

There is a certain hype about “Tensor Flow” as we all know about , and if we go to see why wont there be a hype about a package that google decides to freely release?

What is tensor flow and why did it come into existence?     Tensor flow is nothing but a simple computational package used for machine learning. In vague terms imagine a place where everything is in the form of a matrix, and you perform computations on them to get your result.

It came into existence especially to deal with media content , training a machine to learn from images or audio or video requires a special faster mechanism.Another amazing thing about tensor flow is that makes use of your GPU for training.

You can read more about tensor flow here

We will make use of tensor flow to do some complex things , but as always begin from scratch.

The first thing is installation of tensor flow

For Python ->

You can read installation instructions here. Note – If you are using windows, you may run into a problem. If you do try using docker.

For R->

You can read R installation instructions here.

All the tensor flow examples in this blog will be on python. However if you understand tensor flow in python you can easily implement it in R.

You can validate your installation of tensor flow , by using the following code

import tensorflow as tf
hello = tf.constant('Hello, TensorFlow!',name="My_Tensor",shape=(2,2))
sess = tf.Session()
print(sess.run(hello))
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