Machine learning topic is definitely popular these days. Some get wrong assumptions about it – they think machine could learn by itself and its kind of magic. The truth is – there is no magic, but math behind it. Machine will learn the way math model is defined for learning process. In my opinion, the best solution is a combination of machine learning math and algorithms. Here I could relate to chatbots keeping conversational context – language processing can be done by machine learning with neural network, while intent and context processing can be executed by programmable algorithms.
If you are starting to learn machine learning – there are two essential concepts to start with:
This post is focused around regression, in the next posts I will talk about classification.
Regression is a method which calculates the best fit for a curve to summarize data. Its up to you which type of curve to choose, you should assume which type will be most suitable (this can be achieved with trial and error too) based on given data set. Regression goal is to understand data points by discovering the curve that might have generated them. Read the complete article here.
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