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Tochukwu E.Software Developer, Nigeria
$27 /hr
8 Years Exp.
0 Followers
I am an Oracle Certified Java SE programmer
Junel A.Software Developer, Philippines
$1 /hr
3 Years Exp.
0 Followers
I work at a startup for 3yrs
Kewal Proofreader, India
$4 /hr
4 Years Exp.
0 Followers
Proofreader by profession with 4+ years of experience in Proofreading various types news paper ads, magazines, books, planner and many more from dif...Read More
Having 7 years Experienced System Engineer with a demonstrated history of working in the Computer Hardware industry. Skilled in Giving Technical Advic...Read More
Shishir R.Business Analyst , India
$94 /hr
6 Years Exp.
0 Followers
I am a Web development expert with over 6 years experience in setup and customization of WordPress, Joomla, Shopify, Spree Commerce,Software Developme...Read More
Shubham Software Developer, India
$4 /hr
0 Years Exp.
0 Followers
I am a novice software developer with specialisation in iOS and a competent competitive programmer. Have also done some projects on front end web deve...Read More
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Python is one of the fastest growing programming languages. It has undergone more than 28 years of the successful span. Python itself reveals its success story and a promising future ahead. Python programming language is presently being used by a number of high traffic websites including Google, Yahoo Groups, Yahoo Maps, Shopzilla, Web Therapy, Facebook, NASA, Nokia, IBM, SGI Inc, Quora, Dropbox, Instagram and Youtube. Similarly, Python also discovers a countless use for creating gaming, financial, scientific and instructive applications.

 

Python is a fast, flexible, and powerful programing language that's freely available and used in many application domains. Python is known for its clear syntax, concise code, fast process, and cross-platform compatibility.

 

Python is considered to be in the first place in the list of all AI and machine learning development languages due to the simplicity. The syntaxes belonging to python are terribly easy and can be easily learn. Therefore, several AI algorithms will be easily implemented in it. Python takes short development time as compared to different languages like Java, C++ or Ruby. Python supports object oriented, functional as well as procedure oriented styles of programming. There are lots of libraries in python that make our tasks easier.

 

Some technologies relying on python:

Python has become the core language as far as the success of following technologies is concerned. Let’s dive into the technologies which use python as a core element for research, production and further developments.

 

  1. Networking: Networking is another field in which python has a brighter scope in the future. Python programming language is used to read, write and configure routers and switches and perform other networking automation tasks in a cost-effective and secure manner.
  2. Big Data: The future scope of python programming language can also be predicted by the way it has helped big data technology to grow. Python has been successfully contributing in analyzing a large number of data sets across computer clusters through its high-performance toolkits and libraries.
  3. Artificial Intelligence (AI): There are plenty of python frameworks, libraries, and tools that are specifically developed to direct Artificial Intelligence to reduce human efforts with increased accuracy and efficiency for various development purposes. It is only the Artificial Intelligence that has made it possible to develop speech recognition system, interpreting data like images, videos etc.

 

Why Choose Python for Artificial Intelligence and Machine Learning?

Whether a startup or associate MNC, Python provides a large list of benefits to all. The usage of Python is specified it cannot be restricted to only one activity. Its growing popularity has allowed it to enter into some of the most popular and complicated processes like artificial intelligence (AI), Machine Learning (ML), natural language process, data science etc. The question is why Python is gaining such momentum in AI? And therefore the answer lies below:

 

Flexibility: Flexibility is one of the core advantages of Python. With the option to choose between OOPs approach and scripting, Python is suitable for every purpose. It works as a perfect backend and it also suitable for linking different data structures together.

 

Platform agnostic: Python provides developer with the flexibility to provide an API from the existing programming language. Python is also platform independent, with just minor changes in the source codes, you can get your project or application up and running on different operating systems.

 

Support: Python is a completely open source with a great community. There is a host of resources available which can get any developer up to speed in no time. Not to forget, there is a huge community of active coders willing to help programmers in every stage of developing cycle.

 

Prebuilt Libraries: Python has a lot of libraries for every need of your AI project. Few names include Numpy for scientific computation, Scipy for advanced computing and Pybrain for machine learning.

 

Less Code: Python provides ease of testing - one of the best among competitors. Python helps in easy writing and execution of codes. Python can implement the same logic with as much as 1/5th code as compared to other OOPs languages.

 

Applications of Python:

There are so many applications of Python in the real world. But over time we’ve seen that there are three main applications for Python

Web Development: Web frameworks that are based on Python like Django and Flask have recently become very popular for web development.

Data Science (including Machine Learning): Machine Learning with Python has made it possible to recognize images, videos, speech recognition and much more.

Data Analysis/Visualization: Python is also better for data manipulation and repeated tasks. Python helps in the analysis of a large amount of data through its high-performance libraries and tools. One of the most popular Python libraries for the data visualization is Matplotlib.

 

The global demand for data Science professionals is extremely high because of increasing relevance across various sectors. Data Science has become the most-sought skill because the data is piling along with a surge in different tech fields like Artificial Intelligence, machine learning and data Analytics. Hiring data scientist is being carried across numerous domains like e-commerce, education, retail, telecommunication and much more.

 

In the past years, analysts used excel tools to analyze data. Things are changing now! In this modern world, data-driven decision making is sparkling and technology is advanced in the data industry. The tools and technologies that modern Data Scientists employ are a combination of statistical and Machine Learning algorithms. They are used to discover patterns using predictive models. The future of Data Science is bright and the options for its implementation are extensive.

 

Data Scientists must consistently evolve at the edge of innovation and creativity. They must be aware of the types of models they create. These innovations will allow them to spend time discovering new things that may be of value. Subsequently, the advances in Data Science tools will help leverage existing Data Science talent to a greater extent.

 

So what does a Data Scientist do?

Data Scientists influence a pile of data in an innovative way to discover valuable trends and insights. This approach helps to identify opportunities by implementing research and management tools to optimize business processes by reducing the risks. Data Scientists are also responsible for designing and implementing processes for data mining, research and modeling purposes.

 

Data scientist performs research and analyses data and help companies flourish by predicting growth, trends and business insights based on a large amount of data. Basically, data scientists are massive data wranglers. They take a vast data and use their skills in mathematics, statistics and programming to scrub and organize the information. All their analysis combined with industrial knowledge helps to uncover hidden solutions to business challenges.

 

Generally, a data scientist needs to know what could be the output of the big data he/she is analyzing. He/she also needs to have a clearly defined plan on how the output can be achieved with the available resources and time. Most of all the data scientists must know the reason behind his attempt to analyze the big data.

 

To achieve all of the above, a data scientist may be required to:

 

Every organization has unique data problems with its own complexities. Solving different Data Science problems requires different skill sets. Data Science teams are groups of professionals with varied skill sets. They, as a team, solve some of the hardest data problems an organization might face. Each member contributes distinctive skill set required to complete a Data Science project from start to finish.

 

The Career Opportunities:

The careers associated with data science are generally categorized into five.

 

  1. Statisticians: Statisticians work usually for national governments, marketing research firms and research institutes. Extracting information from massive databases through numerous statistical procedures is what they do.
  2. Data Analyst: Telecommunication companies, manufacturing companies, financial companies etc. hire data scientists to analyze their data. A data analyst keeps track of various factors affecting company operation and make visual graphics.
  3. Big Data and Data Mining Engineer: Tech companies, retail companies and recreation companies use data scientists as data mining engineers. They have to gather and analyze huge amounts of data, typically from unstructured information.
  4. Business Intelligence Reporting Professional: They work for tech companies, financial companies, and consulting companies etc. Market research is the primary objective of this job. They also generate various reports from the structured data to improve the business.
  5. Project Manager: A project manager evaluates data and insights fetched from the operational departments and influences the business decisions. They have to plan the work and make sure everything goes in accordance with the plan.

If you’ve any idea or concept of application and you decide to build your application concept in best programming language, Python is on top of the table. But you may be asking yourself,

What exactly can I use Python for?”

The app development market is greedy but flexible. Trends define the need, and needs define actual trends. Python is now a trend, no doubt about it. Python is also really friendly, thanks to its popularity and the helpful community.

Python is so good, rather than describing what it can do, it’s actually faster to say what Python can’t do. Python is a high-level general purpose programming language that gives multiple paradigms like object-orientation, and structural and functional programming for software development. It works on cross-platform operating systems and may be used across to develop a wide range of applications including those intended for image processing, text processing, web, and enterprise level using scientific, numeric and data from network. According to Stack Overflow, Python is the fastest-growing programming language in the world, and it will still grow even faster. It’s already well recognised as a really universal, versatile, stable, and easy to learn programming language.

The growth rate of python wasn't something easy to realise. There are various attributes of python programming tool which has provided it with a tremendous successful journey. Python features a major role in the latest technologies of current and future times like machine learning and artificial intelligence. 

Who uses Python

Python is used almost everywhere. Just take a glance at the following list (which isn't exhaustive). the purpose is that Python will apply to whatever you’re interested in, no matter what it is.

  • In internet search: Google used Python everywhere in its early development phase.
  • In Space: The International Space Station’s Robonaut 2 robot uses Python for its central command system. Python is planned to be used during a European mission to Mars in 2020 to gather soil samples.
  • Physics Laboratory: Python helps understand the data analysis from some atom smashing experiments at the CERN Large Hadron Collider.
  • In astronomy: The MeerKat astronomical telescope array (the largest astronomical telescope within the Southern Hemisphere) uses Python for its control and monitoring systems.
  • In movie studios: Industrial Light and Magic (Star Wars geniuses) uses Python to automate its movie production processes. Side Effects Software’s computer generated imagery program Houdini uses Python for its programming interface and to script the engine.
  • In games: Activision uses Python for building games, testing, and analysing stuff. They even use Python to search out people cheating by boosting one another.
  • In music/video industry: Spotify music streaming service uses Python to send you music. Netflix uses Python to make sure movies play (stream) no end. Python is used a lot for YouTube.
  • In medicine: The Nodality company uses Python to handle information that they use to search for a cure to cancer.

What to do with Python

With Python, you'll learn to create such things as a math trainer for practicing your times tables or an easy encryption (a secret code) program. And when you’ve honed your skills over time, there are other things you’ll be able to do, such as:

  • Using Tkinter (or other widget sets), you can write user applications that use graphics rather than just text to interact with the user.
  • You can extend other programs like Blender (a 3D modeling program), GIMP (a 2D photo-retouching program), and LibreOffice (office programs), among many others by writing custom scripts.
  • You can write games with graphics using Tkinter or the Pygame or Kivy libraries.
  • You can use the matplotlib library to draw complex graphs for your math or science courses.
  • You can design a website using web frameworks that are based on Python like Django and Flask have recently become very popular for web development.
  • You can use python libraries for machine learning, data science and data visualization.
  • Using Python scripting you can writing small programs for design automate simple tasks.
  • Using the openCV library, you can experiment with computer vision. People who are into robotics use it to help their robots see and grab things and to avoid obstacles when moving.

Whatever you want it to do, there’s a good chance someone has already written code to do it or to help you to do it yourself.

Application of Python

  1. Web frameworks and web application: Python has been used to create a web frameworks including CherryPy, Django, TurboGears, Bottle, Flask etc. These frameworks provide standard libraries and modules which simplify tasks associated with content management, interaction with database and interfacing with different internet protocols like HTTP, SMTP, XML-RPC, FTP and POP. Plone, a content management system; ERP5, an open source ERP which is employed in aerospace, apparel and banking; Odoo- a consolidated suite of business applications; and Google App engine are some of the popular web applications based on Python.
  2. GUI based desktop application: Python has simple and the ability to work on multiple operating systems which make it a desirable choice for developing desktop-based applications. There are various GUI toolkits available which help developers to create highly functional Graphical User Interface (GUI). The various applications developed using Python includes image processing, graphics design, games, scientific and computational application.
  3. Enterprise and business application: With features that include special libraries, extensibility, scalability and simply readable syntax, Python may be a suitable coding language for customizing larger applications. Reddit, which was originally written in Common Lips, was rewritten in Python in 2005. Python also contributed in a very large part to functionality in YouTube.
  4. Language developement: Python’s design and module architecture has influenced development of various languages. Boo language uses an object model, syntax and indentation, almost like Python. Further, syntax of languages like Apple’s Swift, CoffeeScript, Cobra, and OCaml all share similarity with Python.
  5. Operating systems: Python is usually an integral part of Linux distributions. as an example, Ubuntu’s Ubiquity Installer, and Fedora’s and Red Hat Enterprise Linux’s Anaconda Installer are written in Python. Gentoo Linux makes use of Python for Portage, its package management system.

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