The Language of Machine Learning

The Language of Machine Learning

unveiling the mask of Magic.

Numbers constitute the only universal language. ~ Nathanael West.

According to a legend, Mathematics is the Mother of Machines. From the origin of the invention of the first computer in 1822 to achieving the highest computational power of 1102 petaflops, mathematics is the linchpin of the operation. And today, we are amazed by the miracles of Machine Learning, which only is possible through the involvement of Math.

Math? In ML? The what?

Well, yes. You might wonder if someone is sitting inside your computer and processing all the dumb questions you ask (just kidding :p). Well, it's just some weird calculus and statistics behind it.

Let's just put it with an example, say you're trying to predict the price of CocaCola™ in the coming 40 years, and you have a dataset of costs from the previous 100 years in one hand and a bag of chips in the other. Now, after you're done with your chips, You'll give the data to a model that tells you to save money for buying your favorite cold drink in the future. But how?

The straightforward one you can consider implementing is Linear Regression (Time Series Forecasting is a bit complex, for an example :]). Linear Regression puts a scattered plot between the Independent Variables(like the market and time) and Dependent variables(the price - in this case), then draws a regression line through the data(a linear equation, y=mx+b) so that the Mean Squared Error(average of all the errors squared) is minimum.

Basic Linear Regression Chart

Now, you can extend the Regression line further and predict the values. It is never 100% accurate, but you go closer to the value(so it is called Prediction 🥲).

The Math You Need,

You will be a master of ML if you are good at some important topics of Mathematics, some of which include Statistics, Linear Algebra, Calculus, and Matrices.

With Statistics, you'll have reasonable control over the data; Algebra allows you to transform the data; Calculus for Gradient and Loss functions; and Matrices for studying Images.

Though these are just a few popular topics you've encountered in your schooling, they will be ample enough to move forward.

Until we meet with another story, Sree Teja Dusi.

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