Python-The Best and Ideal Programming Language. In this modern technological era, Python Machine Learning has become the hottest trend. According to Forbes, the growth rate of the Machine Learning patent has been increased by 34% between 2013 and 2017 and hopefully, it is going to further grow in the future.
For research and development in Machine Learning, Python is used as the primary programming language. Python is also alternative for machine learning. According to GitHub, Python has become the top programming language for Machine Learning. To further discuss the importance of Python, we will be focusing on an all-important question in this article, i.e., “Why Python is the Most Appropriate Programming Language for Machine Learning”?
In this guide we will present best programming language for machine learning and artificial intelligence.
Top Reasons Which has Made Python Best-Suited for Machine Learning!
For the research and development purposes in Machine Learning, Python is the most popular and widely adopted programming language. You don’t need to just believe in my words! According to the latest Google Trends, the interest in Python, Machine Learning has increased tremendously while other ML languages like R, Scala, Java, and Julia, etc., are lagging far behind.
Since it has been obvious somewhat that Python is turning into the most well known and commonly used programming language in Machine Learning, the WHY still exists. Now let us try to understand why Python has become so much popular and consequently why it is regarded as the best-suited for Machine Learning. Check out a few reasons below, that might help you to understand more about the importance of Python:
1. Easy to Use:
Nobody wants to come across things or tasks that are excessively complicated. The easy usage of Python has made it an essential part of Machine Learning. It is the simple and easily readable syntax, hence making it loved by both professional developers and experimental students.
The simplicity of the Python refers that developers get enough time to focus on solving the Machine Learning issues instead of spending all their efforts and energy in understanding the technical nuances of the Python language.
Additionally, Python is a supremely efficient program language. Developers can finish a lot of work with fewer lines of codes due to it. Humans can easily understand the Python code, hence making it ideal for the creation of Machine Learning models. When you can extract so much from Python, then what can be the reason to no love it!
2. Multiple Frameworks and Libraries
Although Python is already a very popular and frequently used programming language, it has hundreds of frameworks and libraries, easily accessible by developers. These libraries and frameworks save a lot of time, hence making Python even more popular.
A lot of Python libraries are specifically beneficial for Machine Learning and Artificial Intelligence. Some of them are mentioned below:
- Keras, an open-source library, specifically focusing on deep neutral network experimentation.
- Tensor Flow, a free programming library, is utilized for various ML applications like neural systems (one of the most well known libraries!
- Scikit-learn, a free programming library for Machine Learning containing a few classification, relapse and clustering algorithms identified with it.
3. Community and Corporate Support
Since the introduction of Python in 1990, ample time has been available for the creation of a supportive community. Due to these communities, Python learners get a chance to improve their knowledge about Machine Learning, hence ultimately increasing its popularity. Corporate support has become an important part of making Python successful for Machine Learning. A lot of products are made by utilizing Python by top brands like Google, Facebook, Instagram, Quora, and Netflix, and so on. Google has single-handedly created various Python libraries for Machine Learning like Keras and Tensor Flow, etc.
Because of this help, Python students significantly improve their Machine Learning knowledge, ultimately prompting its greater prevalence and reliability. And that’s not the end! A few resources are accessible online for the advancements of Machine Learning with Python, going from GeeksforGeeks Machine Learning instructional exercises to YouTube instructional tutorials, that are extraordinarily helping the learners.
4. Portable and Extensible
Due to its portability and extensible nature, Python has become a very famous and essential part of Machine Learning. Python enables us to perform a lot of cross-language operations due to it. Numerous Data Scientists incline toward utilizing Graphics Processing Units (GPU) to prepare their Machine Learning models on their machines and the compact idea of Python has made it appropriate for this reason.
Python is supported by many platforms like Windows, Macintosh, Solaris, and Linux, etc. Also, due to its extensible nature, Python can be well integrated with Java, .NET components or C/C++ libraries.
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