10 No-Nonsense Machine Learning Tips for Beginners (Using Real-World Datasets)

Author(s): Mukundan Sankar

Originally published on Towards AI.

Stop Overthinking and Start Building Models with Real-World Datasets

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Do you want to get into machine learning? Good. You’re in for a ride. I have been in the Data field for over 8 years, and Machine Learning is what got me interested then, so I am writing about this! More about me here.

But here’s the truth: Most beginners get lost in the noise. They chase the hype — Neural Networks, Transformers, Deep Learning, and, who can forget — AI — and fall flat. The secret? Start simple, experiment, and get your hands dirty. You’ll learn faster than any tutorial can teach you.

These 10 tips cut the fluff. They focus on doing, not just theorizing. And to make it practical, I’ll show you how to use real-world datasets from the UCI Machine Learning Repository to build and train your first models.

Let’s get started.

Forget deep learning for now. It’s crucial to start with small, simple models. You're not ready for neural networks if you can’t explain Linear Regression or Decision Trees. These simple models work wonders for small datasets and lay a solid foundation for understanding the basics.

We’re using the Boston Housing Dataset. The goal?… Read the full blog for free on Medium.

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Published via Towards AI