Hey everyone! I'm new to programming and currently in college, and I'm really eager to learn Machine Learning from scratch. However, I'm feeling pretty lost and frustrated about where to begin. If anyone experienced in this field can share some guidance on a learning roadmap and any tips from your own experiences, I would greatly appreciate it. Thanks a lot!
2 Answers
I recommend starting with the basics first! Make sure you have a solid foundation in statistics, probability, and some core math concepts. Once you feel comfortable, learn Python and dive into libraries like pandas and NumPy for data manipulation. After that, check out scikit-learn to experiment with simple algorithms like regression and classification. Remember to apply what you learn in practical projects—it’s key to solidifying your understanding!
If I could redo my studies, I would have double-majored in math and computer science. Mastering abstract math makes understanding ML a lot easier. For now, I suggest reading 'An Introduction to Statistical Learning.' Work through all the problems. If you're feeling confident with math, you might find Bishop or Murphy's books more beneficial. Also, try looking at past Kaggle competitions to see successful approaches and replicate them!
That’s tough for me because I struggle with math!