Python/Python.docs at master · vilsijain/Python · GitHub

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What is Python?
Python is a popular programming language. It was created by Guido van Rossum, and released in 1991.

It is used for:

web development (server-side),
software development,
mathematics,
system scripting.
What can Python do?
Python can be used on a server to create web applications.
Python can be used alongside software to create workflows.
Python can connect to database systems. It can also read and modify files.
Python can be used to handle big data and perform complex mathematics.
Python can be used for rapid prototyping, or for production-ready software development.
Why Python?
Python works on different platforms (Windows, Mac, Linux, Raspberry Pi, etc).
Python has a simple syntax similar to the English language.
Python has syntax that allows developers to write programs with fewer lines than some other programming languages.
Python runs on an interpreter system, meaning that code can be executed as soon as it is written. This means that prototyping can be very quick.
Python can be treated in a procedural way, an object-oriented way or a functional way.

Good to know
The most recent major version of Python is Python 3, which we shall be using in this tutorial. However, Python 2, although not being updated with anything other than security updates, is still quite popular.
In this tutorial Python will be written in a text editor. It is possible to write Python in an Integrated Development Environment, such as Thonny, Pycharm, Netbeans or Eclipse which are particularly useful when managing larger collections of Python files.


TensorFlow Library
TensorFlow is a free and open-source software library for dataflow and differentiable programming across a range of tasks. It is a symbolic math library, and is also used for machine learning applications such as neural networks.[4] It is used for both research and production at Google.‍[4]:min 0:15/2:17 [5]:p.2 [4]:0:26/2:17

TensorFlow was developed by the Google Brain team for internal Google use. It was released under the Apache License 2.0 on November 9, 2015.[1][6]

ensorFlow is an open-source software library. TensorFlow was originally developed by researchers and engineers working on the Google Brain Team within Google’s Machine Intelligence research organization for the purposes of conducting machine learning and deep neural networks research, but the system is general enough to be applicable in a wide variety of other domains as well!

Let us first try to understand what the word TensorFlow actually mean!

TensorFlow is basically a software library for numerical computation using data flow graphs where:


nodes in the graph represent mathematical operations.
edges in the graph represent the multidimensional data arrays (called tensors) communicated between them. (Please note that tensor is the central unit of data in TensorFlow).
Consider the diagram given below:


Here, add is a node which represents addition operation. a and b are input tensors and c is the resultant tensor.

This flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API!

TensorFlow APIs

TensorFlow provides multiple APIs (Application Programming Interfaces). These can be classified into 2 major categories:

Low level API:
complete programming control
recommended for machine learning researchers
provides fine levels of control over the models
TensorFlow Core is the low level API of TensorFlow.
High level API:
built on top of TensorFlow Core
easier to learn and use than TensorFlow Core
make repetitive tasks easier and more consistent between different users
tf.contrib.learn is an example of a high level API.