Tensor+Flow=TensorFlow

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With the increase in popularity of machine learning and deep learning among students, the term TensorFlow has also been in demand. So today I am here to tell you briefly about what Tensorflow is, How it is implemented, and why it is important.

Brief history

Tensorflow was developed by Google Brain and it was released under Apache 2.0 license in November 2015. The current stable version of TensorFlow is 2.3.1 and it is a popular GitHub repo with 152k plus stars. TensorFlow is a vibrant, active community of developers with more than 2000 developers actively contributing to the code base. 


What is Tensorflow?


Tensorflow is an end-to-end open-source platform for machine learning.

Tensorflow name itself signifies a meaning, It is made up of two words: tensor and flow. A tensor is the multidimensional array and flow is a graph of operations. 

Internally, TensorFlow uses machine learning algorithms as a working graph in a multidimensional array. Once you have accessed the data in TensorFlow, there is a calculation that needs to be done. Each calculation in TensorFlow is presented as a Data Flow Graph. It is not the same as traditional programs. We prepare graphs with nodes and then they are executed in the form of a session with the data in the Tensors. Each node in the graph represents mathematical performance (add, subtract, multiply, divide, etc.) and each edge represents the multi-item layout that is Tensors. A graph is created and data are processed.


Its Importance?

TensorFlow provides easy to build and deploy machine learning models for a newcomer in machine learning. 
If you are a machine learning researcher, TensorFlow enables you to build state-of-art machine learning models with Keras functional API and model subclassing APIs.
TensorFlow API is available for Python, Java, and Go programming languages.
TensorFlow has a very flexible architecture. It enables easy deployment across different hardware platforms like CPUs, TPUs, and GPUs, and computing devices like desktops, servers, mobile devices, and edge devices.

Tensorflow Everywhere


Google uses TensorFlow to improve its products such as Gmail or doc. Airbnb, for example, uses TensorFlow to separate images and find objects in their set of images. AIRBUS uses TensorFlow to find interesting content on satellite imagery and make it available to its customers. TensorFlow is also used for many good social and financial platforms as PayPal uses TensorFlow to get fraudulent transactions, Twitter uses TensorFlow to use tweets. Therefore, you can see that TensorFlow is a flexible product and is used to develop and export machine learning models by companies in various domains.

You can also check out some of these case studies on the tensorflow.org website.



Isha Mudgal (2018-2022)

Computer Science Department
KIET Group of Institutions

Location: Monthly Wrap KIET Ghaziabad, Uttar Pradesh 201206, India

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