After hearing about creating and implementing a model… what is a machine learning model really and how does it actually work?
In: Technology
Saying a machine learning model is pretty broad.
It’s really any type of mathematical equation or process to group things.
The idea is that you have a bunch of data, you then come up with a model. Then it’s the computer’s task to figure out what to do to best fit the model using initially random numbers.
Once there is a “best” way to fit the model, this is referred to as a trained model.
You can then take a brand new piece of data and see what the trained model thinks about it. Is it accurately placed in a group of like things? Is a number of a field calculated which is close to accurate?
This is a huge field and there are many types of models from k-means to deep learning architectures. It really depends exactly what you want to know.
K-means is a very simple concept if you look into that. It’ll give you a concrete machine learning algorithm that you can either implement yourself with any programming language or you can simply call it from a library.
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