Hey everyone! I'm a college student new to programming and I'm eager to learn Machine Learning from scratch. I could really use some guidance from those experienced in the field. Could anyone share a roadmap for learning it and some tips based on your own experiences? I've been feeling overwhelmed, so any help would mean a lot. Thanks!
3 Answers
Honestly, just typing 'ML tutorial' into Google will yield a ton of resources. But I totally get that you might be looking for a more structured approach. There's definitely a need for a clear progression map in learning Machine Learning!
Start by mastering the basics. Don't rush into advanced topics like neural networks right away. Focus on getting comfortable with Python, understanding some statistics, and familiarizing yourself with data manipulation libraries like NumPy and Pandas. After that, try experimenting with Scikit-learn to create small projects like price predictions or spam detection. Once you feel solid with those, you can move on to frameworks like TensorFlow or PyTorch. Remember to keep your learning enjoyable and don't stress too much about complexity!
Quick question: What's your major?
I'm majoring in Computer Science. I know the basics of Python, SQL, and some front-end stuff, but that's it.