Machine Learning-Why Python is the most popular languageIn this technical world Machine learning is one of the fastest emerging fields. Most of the technology companies are spending heavily in machine learning to enhance their products. Machine learning is an application of artificial intelligence, i.e. AI using which the systems can learn automatically and improve their skills from understanding without being explicitly programmed. In simple words, machine learning is to utilize data to make an intelligent decision. Machine learning is nothing but to identify patterns in the data. If anyone wants to work in machine learning field, it is required for them to learn some particular programming languages and skills. The Machine Learning engineer is needed to extract, process, defines, clean, organize and then understand the data, in order to create an intelligent algorithm. Thus, to implement these intelligent algorithms, the engineers have to choose a specific language such as C, C++, JavaScript, R or Python.

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Nowadays, Python programming has become the choice of every machine learning engineer, as it is easy to understand. There are other programming languages too which are used in implementing a machine learning algorithm such as R, C, C++, and JavaScript, etc. but Python is the most popular language among all. Occasionally, the concept of linear algebra and calculus is so complicated and requires a maximum amount of effort. But a fast implementation in Python supports Machine Learning engineer to implement and validate an idea quickly. The graph shown below represents the various programming languages which are most common in implementing machine learning algorithms. In the context of machine learning, a sharp increase is observed in the popularity of these languages in the past few years. This graph shows that in comparison to other languages Python has made a robust effect on the data scientist by gaining the supremacy of around 75% adaptability.

Python is the top language

            Source: fossbytes.com

Instead from being only simple data processing tool Python has now become a major data analytics tools because around 60% of developers are utilizing Python as their primary language for coding.

Python programming language is one of the most flexible and demanding languages and can be utilized for several purposes. It is general purpose language which supports wide-ranging activities such as web development, artificial intelligence, etc. Due to its various features, Python has added enormous popularity in developing the machine learning algorithms. Let’s have a look at its incredible features:

  • Python is simple and easily understandable language.
  • Python contains simple syntax due to which it is easy to learn and use.
  • Python is free and open source language.
  • It is user-friendly and high-level programming language.
  • Python is a portable language because of its open-source nature. The Python programs can be smoothly run on different platforms such as Windows, Linux, Unix, etc. without making any changes in the program.
  • Python supports for the Object-oriented language and thus the concepts of classes and objects come into reality. It also supports procedure-oriented programming, i.e., the programs are created around procedures or functions.
  • The Python programming language contains an extensive and broad Python library which provides a rich set of functions and modules for rapid application development.
  • Python is an interpreted language, i.e. the code in the Python language executes line by line at a specific time; this helps the beginners to debug the code easily.
  • It is easy to integrate Python programming language with other programming languages such as C, C++, JAVA, etc.
  • Python programming language is extensible; this means that languages such as C and C++ can be used to compile the code and thus it can be used in Python code further.
  • With the help of Python programming language, it is easy to develop a graphical user interface.

Reasons for using Python Programming Language in machine learning:

Python programming language offers a big list of benefits to all size of companies, no matter whether it is a startup or an MNC. The practice of Python is not only restricted to a single activity, because of its increasing popularity it is now entering into some of the most popular and complex processes such as Artificial Intelligence, Machine learning, Natural Language Processing, etc. Because of the following reasons, Python is becoming much more popular among the developers.

1. Wide-ranging Collection of Libraries: The Python programming language contains a vast set of libraries and frameworks which simplify coding and thus save a lot of development time. The libraries play an essential role while working on a significant project. Python programming language has an outstanding collection of libraries like NumPy, which is generally used for scientific calculation. SciPy for advanced computation and scikit-learn is used for machine learning applications, Pybrain for machine learning and Django for web development, and ntlk for natural language processing. Also, there are some libraries like tools which offer cross-platform support and provide a significant benefit. Using these pre-built libraries, the developers can save project implementation time.

2. Plenty of support: Due to its open-source feature, a lot of resources and high-quality documentation are supporting the Python programming language. There is a large and active developer’s community who are willing to provide support and advice to the other developers throughout all the phases of the development process.

3. It’s Simplicity: Python programming language is famous for its short and readable code. It is nearly unequaled when it comes to the ease of use and simplicity, mainly for new developers. The developers do not have to worry about the details of coding because machine learning depends on extremely complex algorithms and multi-stage workflow. The syntax is simple in Python which means that it is faster in development than other programming languages and enables the programmer to test the algorithms quickly.

4. Flexibility: Python programming language offers flexibility to the developers. Python is suitable for every purpose and has an option to select between the Object-oriented programming method and scripting. It is possible to link different data structure together in Python, and also it works as a perfect back-end language. Python provides an option of verifying the majority of code in the IDE itself, which is one of the most significant benefits for developers who find difficulty in implementing algorithms.

5. Less coding: Machine learning involves various algorithms, and it is sometimes difficult to implement all of them. Python programming language provides a secure and comfortable testing environment due to which it is one of the top programming languages between developers and programmers. It is possible to write and execute all the codes quickly and effectively using Python. In comparison to other languages such as Object-oriented based programming languages, Python can implement the similar logic with as much as one-fifth of the code. Thus, Python has become the first choice of most of the businesses for machine learning projects.

6. Python is reliable and efficient: The developer’s feels that Python is a quick, consistent and useful language. It is easy to create and deploy Python in any environment. It is a multipurpose language, i.e., you can also work across various domains including web development, desktop applications, mobile applications, etc.

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Conclusion: Presently, Machine Learning is used in most of the organizations for improving their products. In order to implement Machine Learning projects, the Python programming language is gaining much more popularity between millions of developer’s globally. Python programming language has provided several features such simplicity, flexibility, easy to learn and understand which are attracting the new developers to use it for implementing Machine Learning projects. Because of its pre-built libraries, it is possible for the developers to make the Machine Learning projects much more advanced.

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