Learning ML as a PM

If you're like me, you're always looking for new ways to learn and grow in your career as a PM. I took some introductory classes in AI as an undergraduate student but found myself digging deeper into ML and AI and craving to find ways to apply my learnings as a PM. Especially with recent developments in language learning models such as GPT-3 and MT-NLG, I thought it would be a great time to restart my learning and get my hands dirty with some code!

When I began googling resources, I saw several (pretty expensive) classes and seminars advertised to me, but Kaggle is a great free resource that I decided to use instead. With Kaggle, many different courses, tutorials, forums, and other resources helped me get started and continue learning ML. Their introductory ML course explains some core concepts such as how models work (using an example from real estate data), basic data exploration, to building and validating your first ML model.

Kaggle’s Intro to ML course also covers concepts like underfitting vs overfitting in relation to models!

Another cool part of Kaggle is that there are always new competitions and datasets to explore, which means there's always something new to learn. And even if you don't win a competition, just participating can be a great way to improve your skills.

One note is that it is helpful to have some technical background or coding experience before digging into Kaggle’s ML courses since an intro to python isn’t provided as part of the course; however, it’s not extremely necessary since ample examples are shown throughout the coding exercises.

If you're looking for a way to learn ML, (especially as a PM who just wants to gain knowledge of key ML concepts) Kaggle is a great option. With its wealth of resources and supportive community, Kaggle is perfect for anyone who wants to learn more about machine learning.

The learning (get it? :)) shouldn’t stop there though! Here are a few other resources that I think are great to learn about ML as a PM:

Amulya Kandikonda