Author(s): Aleti Adarsh Originally published on Towards AI. Have You Ever Wondered Why Some AI/ML Freelancers Succeed While Others Struggle? This member-only story is on us. Upgrade to access all of Medium. Let’s be real — getting into AI/ML freelancing sounds exciting, right? The idea of working on cutting-edge projects, making money while sipping coffee at your favorite cafe, and having the freedom to choose what you work on? Dreamy. But here’s the thing — this field is CROWDED. Like, ‘everyone and their cat is learning Python’ crowded. So, how do you stand out? I’ve been there, trying to land gigs in AI/ML, only to realize that having a certification or completing a few courses on Coursera isn’t enough. Clients don’t just want an ‘AI engineer’ — they want a problem solver. Someone who can take messy, real-world data and turn it into something valuable. This article is going to be your roadmap. Whether you’re just starting out or struggling to land high-paying gigs, I’ll walk you through how to build standout projects that scream, ‘Hire me now!’ Let’s start with some tough love. If you’ve been applying for freelancing gigs and hearing crickets, you’re probably making one (or more) of these mistakes: Your portfolio is just a bunch of tutorial projects If your GitHub is filled with Titanic survival predictions and MNIST digit classifiers, we… 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
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