Machine Learning doesn& #39;t need to be overwhelming.

Here is a strategy that you can use to get started without too many distractions.

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If you start today, you& #39;ll probably feel overwhelmed by how much —apparently— you need to understand.

But it doesn& #39;t need to be like that.

You can take a much more practical approach to learn what you need and start providing value right away.

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Instead of starting "from the beginning," you can hack your way "from within."

The idea is simple:

1. Pick a simple problem —or an area— that& #39;s interesting to you.

2. Take the necessary steps to learn how to solve that problem.

3. Keep adding complexity as you see fit.

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A "simple problem" always starts with some data.

Look around your organization, and they are likely collecting some data already.

(Even accessing Google Analytics data is a great start!)

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Once you get the data, you want to start asking questions about it.

I got started with the check data of customers of a restaurant.

I decided to answer questions like this: "What did those who bought a beer have for dinner?"

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Answering that question led to even more interesting questions.

It also put me on a path to start learning and proving value since the very first day!

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Here are some other interesting questions I worked on:

https://abs.twimg.com/emoji/v2/... draggable="false" alt="▫️" title="Weißes kleines Quadrat" aria-label="Emoji: Weißes kleines Quadrat"> What& #39;s the preferred beer for those who bought burgers?

https://abs.twimg.com/emoji/v2/... draggable="false" alt="▫️" title="Weißes kleines Quadrat" aria-label="Emoji: Weißes kleines Quadrat"> Who spends more? Those who buy appetizers or those who don& #39;t?

https://abs.twimg.com/emoji/v2/... draggable="false" alt="▫️" title="Weißes kleines Quadrat" aria-label="Emoji: Weißes kleines Quadrat"> What& #39;s the single appetizer that leads to a larger spend?

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Unless you have access to some data already, starting with a valuable problem will be a little bit hard.

You can always tackle a toy exercise, but finding the right one is not always easy.

If you are stuck, consider focusing on a specific area instead.

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Here are a few areas that you can choose to get started:

https://abs.twimg.com/emoji/v2/... draggable="false" alt="▫️" title="Weißes kleines Quadrat" aria-label="Emoji: Weißes kleines Quadrat"> Defecting defects using pictures
https://abs.twimg.com/emoji/v2/... draggable="false" alt="▫️" title="Weißes kleines Quadrat" aria-label="Emoji: Weißes kleines Quadrat"> Answering questions automatically
https://abs.twimg.com/emoji/v2/... draggable="false" alt="▫️" title="Weißes kleines Quadrat" aria-label="Emoji: Weißes kleines Quadrat"> Detecting specific objects in a picture
https://abs.twimg.com/emoji/v2/... draggable="false" alt="▫️" title="Weißes kleines Quadrat" aria-label="Emoji: Weißes kleines Quadrat"> Forecasting your financial position
https://abs.twimg.com/emoji/v2/... draggable="false" alt="▫️" title="Weißes kleines Quadrat" aria-label="Emoji: Weißes kleines Quadrat"> Recommending products based on purchases

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Narrowing your focus to a specific area will help direct your attention to what& #39;s really important.

Remember:

You want to add knowledge in a very intentional manner. One step at a time, as it& #39;s needed to move forward.

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And, of course, there& #39;s nothing wrong with the traditional top-down approach.

Or with any other way you decide to follow.

The only important thing is that you stay consistent and keep providing value!
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