Hey guys,

Just wanted to share that I've completed the "Supervised Machine Learning" course by Andrew Ng on Coursera! I dove into the basics of algorithms and model evaluation tailored for beginners, and I really feel like I've got a solid grasp on the core concepts of ML now.

I'm pumped to keep this momentum going and dive into the next set of courses in the "Machine Learning Specialization" 🚀

Throughout the course, I kept detailed but quick notes to help reinforce my learning.
They're not super organized, as they were more for my own use, but I've decided to share them here in case they might be helpful to someone else.
Here are the notes — feel free to take a look:

The category page: https://geekcoding101.com/category/genai/machine-learning/

Supervised Machine Learning – Day 1

Supervised Machine Learning – Day 2 & 3 – On My Way To Becoming A Machine Learning Person

Supervised Machine Learning – Day 4 & 5

Supervised Machine Learning – Day 6

Supervised Machine Learning – Day 7

Supervised Machine Learning – Day 8

Supervised Machine Learning – Day 9

Supervised Machine Learning – Day 10

Supervised Machine Learning – Day 11 & 12

https://preview.redd.it/ooaihyonf40d1.jpg?width=1024&format=pjpg&auto=webp&s=d47b0387c4122891b8109d8262691a1ee8924ce4