Build a Verifiable ML Portfolio in 90 Days With No Prior Work

AI Summary · Perspective of a Serial Entrepreneur (The following content is distilled by AI; all views belong to the original author. Read this and you won't need to read the full article.)

This is the methodology for ML engineers with no prior experience to land clients. The key numbers: initial prediction error of 40%, brought down to 6% after adjustments (verified in practice), with a 90-day timeline to build a targeted demo. When it comes to generating revenue, the core move is to drop the "resume-style portfolio" and instead deliver a business-value demo that a non-technical person can validate in five minutes. The biggest trap is falling into technical perfectionism and ignoring the actual commercial pain point. Action item: pick one clearly nameable pain point, build a single high-value demo using public data, and deploy it live.

• Name the business pain point in one sentence — ditch the jargon
• Build only one high-value demo, deployed to a publicly accessible URL
• Show "solving a business problem," not "how deep your tech stack goes"
• Use synthetic data or your own logs to generate a demonstrable dataset
• Ask clients about their business workflows directly, proving understanding over credentials

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