# ARTIFICIAL INTELLIGENCE MINDSET

### Why machine learning ?

Think of machine learning as a human, and as a user of technology, you complete certain tasks that require you to make a decision for something. For example, when you read your inbox in the morning, you decide to mark that ‘Help me transfer \$1M out of my country’ email as spam. How would a computer know to do the same thing? Machine learning is comprised of algorithms that teach computers to perform tasks that human beings do naturally on a daily basis.

The first attempts at artificial intelligence involved teaching a computer by writing a rule. If we wanted to teach a computer to make recommendations based on the weather, then we might write a rule that said: IF the weather is cloudy AND the chance of rain is greater than 50%, THEN suggest taking an umbrella. The problem with this approach used in traditional expert systems, however, is that we don’t know how much confidence to place on the rule. Is it right 50% of the time? More? Less?

lets take a more detailed example:

Suppose you go shopping for mangoes one day. The vendor has laid out a cart full of mangoes. You can handpick the mangoes, the vendor will weigh them, and you pay according to a fixed \$ per Kg rate

Obviously, you want to pick the sweetest mangoes for yourself (since you are paying by weight and not by quality). How do you choose the mangoes?

You remember your mother saying that bright yellow mangoes are sweeter than pale yellow ones. So you make a simple rule: pick only from the bright yellow mangoes. You check the color of the mangoes, pick the bright yellow ones, pay up, and return home. Happy ending?

Nope.

Suppose you go home and taste the mangoes. Some of them are not sweet as you’d like. You are worried. Apparently, your mother’s wisdom is insufficient. There is more to mangoes than just color.

After a lot of shopping around (and tasting different types of mangoes), you conclude that the bigger, bright yellow mangoes are guaranteed to be sweet, while the smaller, bright yellow mangoes are sweet only half the time.

You are happy with your findings, and you keep them in mind the next time you go mango shopping. But next time at the market, you see that your favorite vendor has gone out of town. You decide to buy from a different vendor, who supplies mangoes grown from a different part of the country. Now, you realize that the rule which you had learnt (that big, bright yellow mangoes are the sweetest) is no longer applicable. You have to learn from scratch. You taste a mango of each kind from this vendor, and realize that the small, pale yellow ones are in fact the sweetest of all.

Now, a distant cousin visits you from another city. You decide to treat her with mangoes. But she mentions that she doesn't care about the sweetness of a mango, she only wants the most juicy ones. Once again, you run your experiments, tasting all kinds of mangoes, and realizing that the softer ones are more juicy.

Got the idea?

OK.

Why is that important? — very simple its DATA

Data is exactly what machine learning is about, your modern business is all about the DATA you collect from your users; One of the biggest challenges for the modern business is learning to utilize all of the data available to them in a way that is both meaningful and actionable.

### PREDICTION is the KEY!

Learn about your user behavior, how they use your service, how they react to different approaches, when they use your service and when they don’t, why they use it and why they don't — use prediction to save yourself time, human resources and money — prediction is the future but not any prediction; the accurate prediction.

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