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Many companies are now seeking machine learning engineers who can filter through the stacks of data and support them in making the right business decisions. ☛ Data Science and Machine Learningĭata science, analytics, and machine learning are evolving at a prolific rate. Some of the known online products created in Python are Plone (Content Management System), Zope application server, Quixote web framework, and ERP5, an open-source enterprise solution used in the aerospace field. These frameworks deliver essential features to simplify tasks related to content management, accessing a backend database, and handling network protocols like HTTP, SMTP, XML-RPC, FTP, and POP. And you can become one of them by learning frameworks (WAF) like Django, Flask, CherryPy, and Bottle, which give extensive support for web development. Many employers look for full-stack programmers who know Python. Python has the lion’s share in the field of web development. If you wish to go to the Python tutorial section, then click here.īack to top Python Programming Domains ☛ Web Application Development And then, we can form the actual logic to make the program work. With OOP, it is easy to visualize the complex problem into smaller flows by defining objects and how they correlate. OOP provides an intuitive way of structuring your code, and a solid understanding of the concepts behind it can let you make the most out of your coding. Python primarily follows the object-oriented programming (OOP) design. It is because of such openness that Python has garnered a vast community base that is continually growing and adding value.
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You are free to use it, make amends in the source code, and redistribute, even for commercial interests.


It can even exchange data over networks using protocols like SOAP, XML-RPC, and CORBA.
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It allows mechanisms like loading of C and C++ libraries or vice-versa, integration with Java and DotNET components, communication using COM/Silverlight, and interfacing with USB devices over serial ports. Python has several ways to support the cross-application communication. Onc such component could be a Python script while others be a program written in languages like Java/C++ or any other technology. Some applications require interaction across different components to support the end to end workflows. Python Libraries for Data Science and Machine Learning ☛ Component Integration You can load them as and when needed to use the desired functionality.
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of the prebuilt and portable set of libraries. So, you never need to change a line in your code. Also, Python’s interpreter is smart enough to execute your program on different platforms to produce the same output. Since Python is an interpreted language, so the interpreter has to manage the task of portability. Unlike compiled languages, Python programs don’t need compiling and linking, which further boosts the developer’s productivity. It implies there is less to type, limited to debug, and fewer to maintain.
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Python code is significantly smaller than the equivalent C++/Java code. A simple assignment binds a name to an object of any type. It uses an english-like syntax and is dynamically-typed. Python has a clean and elegant coding style. Thus, the name Python struck his mind as not only has it appealed to his taste but also his target users. And more importantly, he was fond of watching the famous comedy series. Guido initially thought the Unix/C hackers to be the target users of his project. And we all know that it was none other than Python, which gradually transformed into a full-fledged programming language. He originally wanted to create an interpreter, a descendant of the ABC programming language of which he was a contributing developer.

He started working on it as a weekend project utilizing his free time during Christmas in Dec’1989. In his own words, Guido revealed the secret behind the inception of Python. Since then, it has grown to become one of the most polished languages of the computing world. It was a Dutch programmer, Guido Van Rossum, who wrote Python as a hobby programming project back in the late 1980s.
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The below sections cover Python history, features, domains, why to learn Python, how to install and run Python on platforms like Windows, Linux, and Mac OS X. This tutorial would make you apt and apply this knowledge to your live projects.

Even a beginner can refer to it and learn Python with least efforts, without investing a lot of time. We’ve organized this course to provide depth, detail, and degree. It has a clean and english-like syntax which requires less coding and let the programmer focus on the business logic rather than thinking about the nitty-gritty of the language. Python is easy to learn, highly readable, and simple to use. However, you may directly jump on to the Python tutorial section. If you are a beginner to Python programming, then we highly recommend you to learn with the flow of this tutorial.
