7 Mistakes Beginner ML Students Make Every Year

Author(s): Boris Meinardus

Originally published on Towards AI.

Don’t study LLMs! You’re making a mistake!

I have received a lot of DMs from people asking me for advice on how to learn machine learning. So in this post, I thought I would talk through 7 of the top mistakes I see beginner machine learning students making every year.My goal for this post is if even one student reading manages to avoid any one of these 7 mistakes, then this post will have been absolutely worth making! So stick around, because the last mistake might be something you are doing already and think is actually good!

Now, I know, I know, we all want to work straight away on the latest and greatest technologies, which all work with Neural Networks. In other words, we all want to get directly into Deep Learning. But this is really a mistake if you want to take studying Machine Learning seriously and get a job in AI. Machine Learning fundamentals are not 100% the same as Deep Learning fundamentals and are perhaps even more important.

You see, AI is just the most general term for decision-making algorithms and does not necessarily mean ML. In fact, as far as I know, AI itself is a bit difficult to define. But a subset of… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI