Hello
I’m new to the field of machine learning and find it challenging to understand some of the foundational concepts. I’ve gone through a few beginner tutorials, but I still feel overwhelmed by terms like supervised vs. unsupervised learning, neural networks, and algorithms like decision trees and k-means clustering.
I’m trying to learn from online courses and articles, but sometimes the material feels too advanced without proper grounding in the basics.
I’m not sure where to start—should I focus more on statistics and programming before diving into machine learning concepts, or is there a better learning path for absolute beginners? Checked https://developers.google.com/machine-learning/crash-course-selenium guide for reference but still need advice.
Any suggestions on structured resources, or explanations in simpler terms that can help bridge the gap between basic programming knowledge and machine learning?
Thank you !