One can barely assert the term ‘machine learning’ without conjuring up images of arcane mathematics, powerful algorithms, and cutting-edge technologies. And these are indeed distinct in the field of Machine Learning.
Given all this, it isn’t startling that there’s been an expansion in the number of machine learning jobs and the excitement for them in the prominent intuition. There are two crucial competitors, Python vs. Java for machine learning.
Both languages have similarities and disparities which makes it riskier to choose one out of the two. The most widespread question asked by the programmers is that if Python is better than Java. So, let’s begin the comparison and find out the winner in Java vs Python.
Nobody likes excessively complicated things and so the ease of using Python is one of the main reasons why it is so popular for Machine Learning. It is easy with an effortlessly readable syntax and that makes it well-loved by both seasoned developers and experimental students. The simplicity of Python means that developers can focus on actually solving the Machine Learning problem rather than spend all their time understanding just the technical nuances of the language.
Python is already quite popular and consequently, it has hundreds of different libraries and frameworks that can be used by developers. These libraries and frameworks are really useful in saving time which in turn makes Python even more popular
This is an important reason why Python is so popular in Machine Learning. A lot of cross-language operations can be performed easily on Python because of its portable and extensible nature.
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2. Scripting Language. |
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3. Python is Dynamically Typed |
Now with this, we come to an end of this comparison on Java vs Python. We observed that Python has a slight edge over Java and wins the battle in most of the factors. So, if you have read this, you might have a clear idea about which programming language is better and which one you should opt for.
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