Machine Learning

• It is simply making a computer perform a task without explicitly programming it.
• Nowadays in world every system that does well has a machine learning algorithm at its heart.
• For example, Amazon Product recommendations, Google Search Engine, Facebook, LinkedIn, etc.
• They are efficiently utilizing data collected from various channels which helps them to get a bigger picture of what should they do and what they are doing.

Deep Learning

• It is a class of machine learning algorithms which uses multiple layers to progressively extract higher level features from the raw input.
• For example, in image processing, lower layers may identify edges, while higher layers may identify the concepts relevant to a human such as letters or faces or digits.
• Smart developers choose python because it is particularly suitable for Deep Learning projects because of its simple syntax and make the language accessible to non-programmers. 

Predictive Analytics

• It is the branch of the advanced analytics which encompasses a variety of statistical techniques from machine learning, data mining and predictive modelling.

Advanced Analytics

• It is a part of Data Science that uses high-level methods and their tools to focus on projecting future events, behaviors and trends.
• For advanced analytics data mining is a key aspect of providing the raw data that will be used by both big data and predictive analytics.
• Pandas is the Python Data Analysis Library, used for everything from importing data from Excel spreadsheets to processing sets for time-series analysis.

Exploration and Data Analytics

• It is a phenomenon under data analysis used for gaining a better understanding of data aspects like variables, relationships that hold between them and main features of data.
• Another side benefit of Exploration and Data Analytics is to refine your selection of feature variables that will be used later for machine learning.

Data Science

• It is the study of the data which involves developing methods of recording, storing, and analyzing data to effectively extract useful information.

Statistics

• Python is a general-purpose language with statistics modules in which R has more statistical analysis features than Python, and specialized syntaxes.

Web Applications

• Python is used to develop application and it provides libraries to handle internet protocols such as HTML and XML, JSON, Email processing, request, beautiful Soup, Feed parser, etc.
• Python provides many useful frameworks like Django & Pyramid framework is used for heavy applications, Flask & Bottle is used for Micro-framework, Plane & Django CMS framework is used for Advance Content Management.

Desktop GUI Applications

• The GUI otherwise known as Graphical User Interface which provides a smooth interaction to any applications.
• Python provides Tk GUI library to develop a user interface.
• The popular Graphical User Interface libraries like Tkinter or Tk, wxWidgetM, Kivy, PyQt or Pyside.

Console-based Applications

• In Console-based applications run from the command-line or shell and in which programs are use command to execute.
• In old generation of computers this kind of application was more popular.
• Python is famous for having REPL, which means Read Eval Print Loop that makes most suitable language for the command-line applications.

Software Development

• Python is useful for the software development process and works as a support language.
• It can be used to build control and management, testing, etc.
• In this software development SCons is used to build control.
• In this Buildbot and Apache gumps are used for automated continuous compilation and testing.

Scientific & Numeric

• It is the era of Artificial intelligence where the machine can perform the task the same as the human.
• Python language is most suitable language for machine learning or Artificial intelligence.
• It consists of many scientific and mathematical libraries, which makes easy to solve complex calculations.
• Python has many libraries for scientific and numeric such as Scipy, Scikit-learn, Numpy, Pandas, Matplotib, etc.

Business Applications

• Business Applications differ from standard applications for example, E-commerce and ERP.
• This kind of application requires scalability, readability, extensively and it requires all these features.
• Python provides Tryton platform which is used to develop the business application.

Audio or Video-based Applications

• Python can be used to create multimedia applications and it is flexible to perform multiple tasks.
• Some multimedia applications which are made by using Python are TimPlayer, cplay, etc. and multimedia libraries like Gstreamer, Pyglet, QT phonon.

3D CAD Applications

• The Computer Aided Design (CAD) is used to design engineering related architecture.
• It is used to develop the 3D representation of a part of a system and create a 3D CAD application by using the following functionalities like Fandango, CAMVOX, HeeksCNC, AnyCAD, RCAM.

Enterprise Applications

• Python can be used to create applications that can be used within an organization or an enterprise and some real-time applications are Tryton, OpenERP, Picalo, etc.

Image Processing Applications

• Python contains many libraries that are used to work with the image and it can be manipulated according to our requirements.
• Some libraries of image processing like OpenCV, Pillow, SimpelITK.

Easy

• It is a friendly developer language which means that anyone and everyone can learn to code it in a couple of hours or days.
• Python is one of the easiest to learn, while compared to other object-oriented programming languages like Java, C, C++, and C#.

Free and Open-Source

• It is an open-source programming language which means that anyone can create and contribute to its development.
• It has an online forum where thousands of coders gather daily to improve this language further.
• In any OS like Windows, Linux, Mac it can be use and free to download.

Gui Standard

• GUI is otherwise known as Graphical User Interface is one of the key aspects of any programming language because it has the ability to add flair to code and make the results more visual.
• It is one of most favorite language for developers, so its supports for a wide array of GUIs which can easily be imported to the interpreter.

Object-Oriented Approach

• It is partial object-oriented programming language.
• Basically, python recognizes the concept of class and object encapsulation thus allowing programs to be efficient in the long run.

High-Level Language

• It has been designed to be a high-level programming language, which means that when you code in Python you don’t need to be aware of the coding structure, architecture as well as memory management.

Integrated by Nature

• It is an integrated language by nature which means that the python interpreter executes codes one line at a time.
• We don’t need to compile Python code thus making the debugging process much easier and efficient, unlike other object-oriented programming languages.

Portable

• If we are running Python on Windows and you need to shift the same to either a Mac or a Linux system, then you can easily achieve the same in Python without having to worry about changing the code.

Dynamically typed

• It is one of the most dynamic languages available in the industry today.

Large library standard

• It comes inbuilt with a large number of libraries that can be imported at any instance and be used in a specific program.

Support for Other Languages

• By default, Python supports the execution of code written in other programming languages such as Java, C, and C#, thus making it one of the versatile in the industry.

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