A general-purpose programming language Python was released initially in 1991 and it was designed for optimizing the readability of codes. Now Python is chosen for using for Machine Learning widely across several industries and it is ranked 2nd among the excellent programming languages available. Machine learning internship in Kolkata offered by Graphson Technology can be excellent to develop a brilliant understanding of the possibilities of Python.
What makes Python so popular?
There are valid reasons for the popularity of Python for finding wide use in industries for Machine learning and few important reasons are as follows:
- It is available free: Python is an open-source program that is available free and you can easily download python for use as a programming language. You can access easily to the vast resources available in the libraries of Python that can easily support you to carry all the tasks you want.
- Easy to learn: Python is very simple to understand and it has excellent functionality as well as it is scalable. The code readability can be easy and it comes with a very well structured and versatile language.
- An all-purpose programming language: One of the most interesting features of Python is that it can be easily used for building anything. It is highly useful for Artificial Intelligence, Machine language, scientific computing, web development, Data analysis, etc. It can also be used by the developers to build desktop apps, productivity tools, and games.
- It is very easy to integrate: In many places, Python is also used widely as an integration language and can be very effective to glue the exiting components. With other programming languages like C, C++, and Java, Python can be seamlessly integrated.
Why Python is considered for machine learning?
Many factors go in favor of Python for considering as the best programming language for Machine Learning.
- Amazing collections are available in libraries: The great collections that are available in Python libraries is a good reason for choosing it for Machine Learning. Since Machine Learning requires continuous processing of data, libraries can be very effective to provide access to the immense database. The Scikit-learn, Keras, Tensor Flow, NLTK, StatdModels, etc are some of the examples of wonderful library collections.
- There is very easy entry: Learning python is as easy as learning the English language and all you need to do is to just install Python and start using it. The choice of Machine learning internship in Kolkata can be very helpful to master Python in a short time and to use its vast potential easily.