ML Explained
This isn’t a crash course. There’s no “ultimate guide” here, no promise to make you an expert over a weekend
This corner of the internet is the place where I attempt to teach Machine Learning the way I wish I’d first encountered it… slowly, clearly, and with context that sticks. If you’ve ever googled, “machine learning” and landed on a sea of buzzwords, equations, or flowcharts that left you more confused than enlightened; welcome! You’re not alone. I’ve been there too, and it’s part of why I’m writing this series.
The people that know me well, know that I do not have a good attention span. So I’ll keep things short. This explainer series is not going to be a tutorial or a crash course. It’s more like a conversation. A walk-through of the key ideas, the questions worth asking, and the principles you actually need to understand before you care about the accuracy scores or the latest Transformer papers out there. Like I said earlier, I’d like to keep things short but, not incomplete. Each article will be hopefully short, focused, and designed to build up your intuition over time.
This is not about “Mastering ML in X days”. It’s about learning out loud and learning well.
