Before we dive in, we have to understand that AI projects are different from traditional software projects in terms of the technology stack and skills required. Therefore, hr generalist salary new york choosing a programming language that is stable, flexible, and has a diverse set of tools is so important. Some of the reasons why Python is growing at a supersonic speed.
However, when faced with a choice between the two, the decision should always come down to the individual requirements of your project. PHP is easier to install on any platform than Python, unless you stick exclusively to Linux. The latter does, however, make use of plenty of libraries to make up for that slight inconvenience. Even though PHP has traditionally been more popular than Python, it’s been gradually losing traction of late.
Many of the factors that make python an attractive choice for beginners also set it apart as a reliable option for data-science and data-analysis. Python’s ease of use, support, and flexibility have made it an essential tool for those who work with machine learning, cloud computing, and big data. What is it about Python that seems to capture the interest of developers, new and experienced alike? Here, we take a brief look at nine factors that have helped make Python one of the world’s leading programming languages. Today, apps like Instagram run on Python, and just recently, Facebook made one of its Python-based security projects — Pysa — available as open source.
It’s much easier to use and has a great support system when it comes to AI and ML frameworks. Python can do almost all the tasks as R—engineering, data wrangling, feature selection, web scraping, app development, and so much more. Basically, Python code is easier to maintain and stronger than R. Hence, Python is often used to deploy and implement machine learning at a large scale. Because of this, the programming language offers one of the richest ecosystems for performing data analysis.
No, whitespace indentation depency IS a bad syntax, popularity doesn’t make it good. It’s not about readability it’s about errors that may arise from alterations to the leading white space. For example, it used to be the case that copy/paste in X Windows would change tabs to spaces or trash indentation all together — not good for Python code logic. Syntactically important white space is a bad idea and Python is popular despite this “feature”. I’m more interested in what languages are actually used rather than what are popular darlings. I learned BASIC in 1982 on a Radio Shack TRS-80 in 8th grade math class.
That makes it a challenge to pick one out of the two for your data analytics. Many programmers and data science students are using python language for their development projects. Learning python is one of the important section in data science certification courses. In this way, the python language can provide plenty of fantastic career opportunities for students.