Machine Learning is one of the most important parts of the data-driven economy. If you want to learn machine learning you must be having complete knowledge of what to learn before starting with Machine Learning. In this article, I will take you through the Prerequisites for Machine Learning.
Machine learning teaches computers to do what comes naturally to humans and animals: learning from experience. Machine learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a template. The algorithms adaptively improve their performance as the number of samples available for training increases.
Prerequisites for Machine Learning
To learn machine learning you need to follow a roadmap, but before starting with Machine Learning there are three most important skills that you should know:
The journey towards machine learning starts with learning a programming language. Now generally when you are in schools, you learn C++ or Java, which is very good for beginners to learn the fundamentals of programming.
But when you want to choose a specific career in any field you need to learn a specific language which is best for your task. For example, HTML, CSS, and Javascript for Web Development, VBA for automation, C++ for OS and game development, Java for Android Development, and Python or R for Machine Learning.
Now when you go more in-depth for choosing a language between Python or R, then choose Python because the community behind Python has increased a lot, as a result, you will find a lot of free resources on the internet to learn Machine Learning for free using Python.
Now you don’t need to learn everything in Python to start with Machine Learning, just learn the fundamentals of Python programming language, and then just start with learning Python libraries like Numpy and Pandas with which you will start your journey towards Machine Learning.
I hope you liked this article on the Prerequisites for Machine Learning. Feel free to ask your valuable questions in the comments section below.
