How to effectively showcase your machine learning experience

What to build. How to present your work. How to centralize.

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When it comes to showcasing machine learning experience, many professionals take the approach of listing all their past jobs. Chronologically.

Along with hurting your chances, it does one more thing — makes you look boring.

As a machine learning builder, how do you effectively showcase your machine learning experience? How do you stand out? Here are my thoughts on a better approach to showcase your machine learning experience:

Companies want to recruit builders

Keep it in mind at all times. Anything that shows you can build is an edge. It will make your profile shine. There’s no reason to list everything chronologically. You can arrange the information anyway you want.

Centralize all your work

Make a habit of centralizing all your work in one place. It's as simple as having a personal website that someone can visit to see what you've built over your career.

It should be updated regularly, which means you need to build regularly. It should have a theme, which means you need to pick a specific area to focus on. Let compounding do its magic for you.

Choose the right projects to highlight

Collect all your past work that includes code samples and notebooks. If you don't have anything, you haven't been building.

The good thing is that it's never too late to start building. Do exercises/projects from hackathons, blog posts, or courses. Anything you can get your hands on.

Make sure your exercises are not too basic. If it can be copy-pasted from a library’s documentation page, it's not worth showcasing. Choose the right level of complexity.

Make it publicly accessible

Write clean code and make it publicly accessible. You need a platform where you can run the code on the cloud. Google Colab is a good way to do it. It's a free Jupyter notebook environment and runs entirely in the cloud. No setup needed. Plus you can embed Google Colab notebooks into any webpage. You can showcase your documentation skills as well.

Build like an engineer. Present like a designer.

Present your work well. Goes a long way. Think of it as showcasing a portfolio. How would a designer showcase their portfolio? You should pick your top 10 most exciting projects to list here. Make it appealing.

Go the extra mile — Production readiness

You don't need to go very deep, but find a way to show that you care about building a functioning product. Make your code production ready. Not just a training method in Python. Go the extra mile. Wrap your module in Flask.

Take the steps needed to deploy your models. Many people will just write code to train and test their models. This is an easy way to stand out.