Performance metrics are what we use to judge the performance of our model. There are various performance metrics — accuracy, precision, recall, mean absolute error, mean average error etc.

It is extremely important to know which kind of metric to use — else we will be wrongly judging our model.

In my last post, I had mentioned I will explain how this “training of the model” works. (If you haven’t read it, check it out here — Linear regression and Classification)

So far what we have seen is, we input some data to a “machine learning model”, which in the…

Linear regression is a type of machine learning model which predicts real value output, i.e the output variable is continuous. It is based on supervised learning. …

In my opinion, machine learning is a combination of mathematics and computer science. So of course there is some math that you need to know before we start off with actually making machines learn some data to make accurate predictions! …

Machine Learning has been a buzzword for quite some time now and for good reason. From movie recommendations (Netflix) to spam filtering (Gmail) and personalised cancer care (IBM Watson Genomics), machine learning has pervaded every aspect of our lives.

Consider the picture shown. If I ask you to pick an…

Sonu Ranjit Jacob

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