7 lessons I’ve learned about starting a career in machine learning.

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Right about when the pandemic started, I started helping others divert themselves into machine learning. It was mostly software engineers looking to learn new skills and people migrating from less lucrative careers.

I’ve learned a few things in the process.

These are 7 lessons that I’d like you to keep in mind.

1. Most people love the idea of starting something new. Only a few take the first step.

Getting ready is way more fun than making progress. It’s also relatively useless.

People decide to go to the gym. They buy supplements, shorts, shoes, and a new headband. But they never actually start; there’s always something else they need.

Starting with machine learning is no different. It becomes a race to collect books, tutorials, and the latest and hottest video playlist.

Preparing for something new is fun and exciting. It can also turn into glorified procrastination.

You can’t possibly know what you need before getting started. Take what’s right in front of you and run with it.

2. Learning is a marathon, not a sprint. Strap yourself for a long, lifelong road.

Machine learning is a lifelong journey.

If you are looking to make a quick buck, look elsewhere. If you are looking for shortcuts, this ain’t it.

Solving hard problems requires experience and a lot of hard work. Machine learning is a fast-paced field that’s constantly evolving, and you’ll have to stay on your toes to avoid falling behind.

Make sure you come for the right reasons. Make sure you start with the proper expectations.

3. “If you want to go quickly, go alone. If you want to go far, go together.”

I love this proverb!

Those who pull ahead almost always do it as part of a group.

The community you are part of will have 10 times more influence on your progress than anything else you could do. The constant sharing, accountability, competition, and debate will increase your odds significantly.

Find like-minded people that want to take this journey with you.

4. If you finish a course, and the only thing you have to show for it is inside your head, you wasted your time.

Consuming information will make you smarter for a day, but it will all go away with no practice.

Unfortunately, most people try to cram as many pages of the book as fast as they possibly can. Checking the box becomes all that matters.

This is useless.

You must apply what you learn, solve problems, write a journal, share it with a friend. Teaching is the ultimate way of learning.

5. People think about math every time machine learning comes up. They are missing the point.

Most people are scared about their math skills.

Funny enough, it’s their lack of programming skills that really hold them back. Yes, there’s a lot of math in machine learning, but it mostly stays hidden behind a wall of code.

Here is a much better investment for you: become a good developer.

(Math is important, and here are my recommendations if you are looking to level up, but don’t let it hold you back from getting started.)

AI/ML

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