So many people are learning machine learning. What should you do to stand out?

There it was. Podcasts, YouTube, blog posts, machine learning here there changing this changing that changing it all.

I had to learn. I started. Andrew Ng’s Machine Learning course on Coursera. A bunch of blog posts. It was hard but I was hooked. I kept going. But I needed some structure. I put a few courses together in my own AI Masters Degree. I’m still working through it. It won’t finish. The learning never stops.

Never.

You know this. You’ve seen it happening. You’ve seen the blog posts, you’ve seen the Quora answers, you’ve seen the endless papers the papers which are hard to read the good ones which come explained well with code.

Everyone is learning machine learning.

Machine learning is learning everyone.

How do you stand out?

How how how.

A) Start with skills

The ones you know about, math, code, probability, statistics. All of these could take decades to learn well on their own. But decades is too long. Everyone is learning machine learning. You have to stand out from everyone.

There are courses for these things and courses are great. Courses are great to build a foundation.

Read the books, do the courses, structure what you’re learning.

This week I’m practising code for 30-minutes per day. 30-minutes. That’s what I have to do. When I don’t feel like practicing. I’ll remind myself. These are the skills I have to learn. It’ll be yes or no. It’s my responsibility. I’ll do it. Yes.

Why skills?

Because skills are non-negotiable. Every field requires skills. Machine learning is no different.

If you’re coming from zero, spend a few months getting into the practical work of one thing, math, code, statistics, something. My favourite is code, because it’s what the rest come back to.

If you’re already in the field, a few months, a fear years in, reaccess your skills, what needs improving? What are you good at? How could you become the best in the world at it? If you can’t become the best in the world, combine with something else you’re good at and become the best in the world at the crossover.

B) Got skills? Good. Show them.

Ignore this if you want.

Ignore it and only pay attention to the above. Only pay attention to getting really good at what you’re doing. If you’re the best in the world at what you do, it’s inevitable the world will find out.

What if you aren’t the best in the world yet?

Share your work.

You make a website.

machinelearner.com

I made this up. It might exist.

On your website you share what you’ve been up to. You write an article on an intuitive interpretation of gradient descent. There’s code there and there’s math there. You’ve been working on your skills so to give back you share what you’ve learned in a way others can understand.

The code tab links to your GitHub. On your GitHub you’ve got examples of different algorithms and comments around them and a tutorial on exploratory data analysis of a public health dataset since your interest in health. You’ve ingested a few recent papers and tried to apply it to something.

LinkedIn is your resume, you’ve listed your education, your contributions to different projects the porjects you’ve built the ones you’ve worked on. Every so often you share an update of your latest progress. This week I worked on adding in some new functions to my health project.

You’re getting a bit of traction but it’s time to step it up. You’re after the machine learning role at Airbnb. Their website is so well designed you stayed at their listings you’re a fan of what the work they do you know you could bring them value with your machine learning skills.

You make another website.

whyairbnbshouldhiremeasamachinelearningengineer.com

I made this one up too. Kudos if you’re already on it.

You send it to a few people on the Airbnb recruitment team you found on LinkedIn with a message.

Hi, my name is Charlie, I hope this finds you well.

I’ve seen the Machine Learning Engineer role on your careers page and I’d like to apply.

I made this website which shows my solutions to some of your current challenges.

If you check it out, I’d love your advice on what best to do next.

5/6 of the people you message click on it. This is where they see what you’ve done. You built a recommendation engine. It runs live in the browser. It uses your machine learning skills. Airbnb need a machine learning engineer who has experience with recommendation engines. They recommend a few things.

3 reply with next steps of what to do. The other 2 refer to other people.

How many other people sent through a website showcasing their skills?

0.

Maybe you don’t want a job. Maybe you want to research. Maybe you want to get into a university. The same principles apply.

Get good at what you do. Really good.

Share your work.

How much?

80% skills.

20% sharing.

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