Python is the fastest growing and also among the most popular programming languages in the world. Besides being used in the regular web and app programming, its being extensively used in multiple domains including data sciences and artificial intelligence. As a very versatile, multi-purpose and easy to understand language, it is considered the best language to use for Machine learning.
Machine learning, in simple terms, is recognizing patterns in large amounts of data and then using it to create algorithms and models for computer systems. The computer system then will use it to perform a specific task without being given explicit instructions and rely on the patterns and inferences instead. It is considered to be a division of artificial intelligence and is one of the fastest growing fields in science and technology.
But what makes Python the perfect language for Machine learning? Let’s look at 10 reasons why.
- Easy to understand
Machine learning algorithms are very complex and very hard to create as well as understand. Python, being the simplest programming language, gives a simple learning curve for the beginner to master and the developer can start coding and exploring algorithms and machine learning. Join up a special Machine learning with Python course today to get started.
- Syntax structure
One of the reasons why Python is considered is because it has very simple syntax structure and this allows the developers to test the complex algorithms very quickly without having to spend a lot of implementing it.
- Faster prototyping
Simpler structure means that a lot of time doesn’t need to be spent for the actual coding and this also means that the prototype can be rolled out much quicker thereby reducing the overall time spent for development.
Another advantage of Python is that there are multiple routes and options you can choose from in terms of approach and scripting depending on your need and factors such as data sources giving you more flexibility and helping you link different data together.
Being a very open -ended language, it is used across multiple fields; from artificial intelligence and machine learning to scientific and numeric computing to analytics and data interpretation making it possible for different fields to come together and work on multi- dimensional projects.
- Amazing data handling capabilities
Python may not be built for speed but it sure can handle large amounts of complex data from all kinds of sources. Machine learning is basically being able to recognize patterns in your data and this means that there is a lot of raw data in its most unstructured incomplete state than needs to be interpreted. And since it comes from different sources in different formats it needs to be changed into something that can be recognized by the machine. Python makes it easy to do so with its large collection of code stack of various open source repositories, written by individuals and teams across the world which are always updated and improved up on. This makes interpretation and implementation in any format under the sun, easy and hassle free. And the best part is that you don’t even have to know how it does it. Once you have a basic idea of what you want to do, you can get right into implementing it.
- Large selection of libraries and frameworks
This is pretty much similar to what was being talked about in the earlier point. The number of libraries and frameworks available to users is staggering and makes life that much simpler for everyone who has to use Python for various applications such as scientific computation, advanced computation, data mining and data analysis. It is the case for Machine learning as well. Frameworks like the PyTorch- framework have been specially written for machine learning and it makes coding easier, saving time in development.
Python is the most popular programming language in the world and programmers prefer it over the other languages for its sheer simplicity and it’s the same for ML programmers as well which makes it easier to find an ML programmer who use Python than another language for ML projects. This also means that more and more people are enrolling in Machine learning with Python training to join in on the hype taking over the world by storm.
Being a very popular language, it is supported by a large number of high-quality resources and good quality documentation. This means that the developers are constantly supported and provided advice and assistance at the various stages of development.
Python has millions of users around the world and this means that there exists a large community of Python users who can be found online on various platforms of discussions such as Reddit and happen to be extremely supportive and helpful.
Hope these reasons are compelling enough for you to take up the Machine Learning with Python training soon. Enrol now to forge on a lucrative career.