Machine learning – the process
Machine learning algorithms are trained in keeping with the idea of how the human brain works. They are somewhat similar. Let's discuss the whole process.
The machine learning process can be described in three steps:
Input
Abstraction
Generalization
These three steps are the core of how the machine learning algorithm works. Although the algorithm may or may not be divided or represented in such a way, this explains the overall approach:
The first step concentrates on what data should be there and what shouldn't. On the basis of that, it gathers, stores, and cleans the data as per the requirements.
The second step entails the data being translated to represent the bigger class of data. This is required as we cannot capture everything and our algorithm should not be applicable for only the data that we have.
The third step focuses on the creation of the model or an action that will use this abstracted data, which will be applicable for the broader mass.
So, what should...
