Author(s): Mukundan Sankar Originally published on Towards AI. Stop Overthinking and Start Building Models with Real-World DatasetsThis member-only story is on us. Upgrade to access all of Medium.Photo by Mahdis Mousavi on UnsplashDo you want to get into machine learning? Good. Youre 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 heres 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. Youll 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, Ill show you how to use real-world datasets from the UCI Machine Learning Repository to build and train your first models.Lets get started.Forget deep learning for now. Its crucial to start with small, simple models. You're not ready for neural networks if you cant explain Linear Regression or Decision Trees. These simple models work wonders for small datasets and lay a solid foundation for understanding the basics.Were using the Boston Housing Dataset. The goal? 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 asponsor. Published via Towards AI