The Power of Python in Machine Learning for Beginners : Know about Machine Learning with Python .
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What is the Python language in computing?
Python is the open source programming language most used by computer scientists. This language has propelled itself to the forefront of infrastructure management, data analysis and software development.
Indeed, among its qualities, Python allows developers to focus on what they do rather than how they do it. It freed developers from the constraints of forms that occupied their time with older languages.
Thus, developing code with Python is faster than with other languages. It also remains accessible for beginners, as long as you give it a little time to get started. Many tutorials are also available to study it on specialized websites or on YouTube accounts.
On computer forums, it is always possible to find answers to your questions, since many professionals use it. I/ What is the Python language used for...? The main uses of Python by developers are: 1/the programming of applications 2/the creation of web services 3/code generation 4/metaprogramming. Technically, this language will be used mainly for scripting and automation (interaction with web browsers).
What is the current version of Python?
We distinguish two versions: Python 2 and Python 3. Python 2, the old version offers updates until 2020. Python 3 is the current version. Its interpreter is more efficient, as well as its competition control. The origins of programming language Guido van Rossum, a Dutch developer, invented Python in 1989. He was keen to automate repetitive tasks related to writing computer scripts. The differences between Python 2 and 3 are such that most lines of code written with Python 2 are no longer compatible with Python 3. For example, to display a result with Python, we use the “print” function. With Python 2, the function is written: print 'Hello, World!' With Python 3, the function is written: print('Hello, World!') The purpose of these two instructions is the same: to display the characters that make up the sentence: Hello, World! However, in computing, syntax is very important. This is why Python 3 will not be able to understand and execute the instruction written with Python 2. However, the two versions continue to coexist today but Python 2 is destined to disappear in the coming years. Today, Python 3 has become a very popular language. For example, if you used a Casio or Texas Instrument calculator in high school, your calculations were run using Python 3!. The Tiobe ranking, which lists the most popular and authoritative languages in the world of programming, even places Python in first place since December 2021!
The advantages and disadvantages of Python:
Python is a simple, powerful and easy to learn language. Its first advantage is to use functions in English: if you have some knowledge of English, it will be easy to remember what these functions are for. In addition, the syntax of Python may present some subtleties, it is much less heavy and rigid than that of other languages. For example, you can insert a comment with a simple hashtag (#) at the beginning of the comment, while in Java and C you have to open the comment by/* and do not forget to close it with */. Learning Python is therefore very accessible (even for beginners), and it is often with Python that we start programming. Experienced developers also benefit from the flexibility of the Python language. Simple syntax allows you to write functional programs faster. Indeed, for a line of code to work, it must be correctly written. For example, there is no messaging that prevents you from sending a message that contains spelling errors. Despite the bad experience of the reader, the content of the mail can be understood by whoever receives it. With a programming language, it’s another story: if there is a syntax fault in a line of code, it won’t work. That’s why some developers spend a lot of time debugging their code so that it can work. When starting with a programming language, finding the small fault that prevents the code from working can be a time-consuming and quite discouraging exercise. The simplicity of the syntax of the Python language is a great advantage since it allows you to write lines of code that work or quickly identify what needs to be fixed. Thus, coding in Python allows developers to focus on the purpose of their program, without having to debug their code permanently to fix syntax errors. At the same time, Python is an extremely versatile language that can be used in many contexts. It is useful for programmers, who develop applications and software, as well as for data science professionals. Indeed, Python is compatible with any operating system: Windows, macOS, UNIX, Linux, etc. This versatility does not affect the quality of the language. Python is a powerful and complete language. As long as you are a good developer, Python allows you to carry out any type of project with a high level of requirement. That’s why big companies like Google, Nasa, Microsoft or Instagram (to name a few) use Python. So there are many reasons to learn Python in 2022! In particular, the Python language is an essential part of Data Science. If you are interested in the profession of Data Analyst, mastering Python is a skill that recruiters are looking for. It is also highly appreciated by Data Scientists: the majority of them work with Python on a daily basis. To take your first steps in the world of Data Science, the Databird training gives you the keys to using Python and the best practices to adopt (method, techniques, conventions, etc.). Whether you take the training full-time or part-time, the goal is the same: to become competent enough to be operational in a company in order to get a permanent contract as a Data Analyst. For more information, you can consult the course of our alumni or discover the program of our trainings.
II/ What can we do with Python?
A powerful and versatile language Python has many application domains, unlike HTML or JavaScript, which are only used for web development. With Python, we can: Create and administer a website Develop software and applications for both computers and telephones automate system scripts and computer interactions – web browser. Thus Python makes it possible to write and execute programs with increasing complexity. You can just as easily program a short script loaded with a specific task on your computer, network several professional software programs or even develop a video game… on a calculator! At Databird, we teach our students, “databirdies”, to: Sucking up web data, using Python’s web-scraping features, Write scripts to clean and analyze a database, View results graphically, using Python’s datavisualization features Connect to web services, making a REST API with Python A language complemented by Python libraries If Python is usable in so many domains, it is thanks to the wealth of its libraries (or «libraries»). A Python library brings together functions that have a common theme in one place. These functions do not exist in the original Python package, but they were encoded by developers who put their work in open-source. The Python libraries most used by Data Analyst are: Pandas, which allows you to manipulate and analyze data tables in the manner of an Excel on steroids. NumPy, which allows scientific calculations (especially statistical and probabilistic). Scikit-Learn and Tensorflow, which support the development of machine learning and deep learning models. Scrapy and BeautifulSoup, which allow data to be extracted directly from the Web (called “scraping”). Seaborn and Matplotlib, which help with data visualization, notably by offering graphic construction tools. To use a library, simply import it at the beginning of the program (a line of code is enough). This is very convenient because you can then use all the functions it contains. Note: It is possible that there may sometimes be duplicates, that is, two functions are available in two different libraries and under two different names when they serve the same purpose. The wealth of Python libraries makes it possible to push the boundaries of language and tackle ambitious and demanding projects in many areas of application. For example, in the field of scientific research, the biopython library makes it easier to process and analyze biological data. In video games, the pyGame library is used to create 2D or 3D video games. Python libraries thus participate in the two main forces of language: its simplicity of use, its versatility. The Databird trainings will allow you to take control of the Python libraries and learn how to take advantage of their complementarities to carry out your data projects.
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