After months of building, I’m excited to share Halgorithm — a free, hands-on course platform to help anyone get started with machine learning (even without a math or CS background).
The goal is to fix what I felt was missing in many intro ML resources:
Too much theory, not enough doing
Overloaded with math, too little intuition
Toy datasets, no real-world messiness
The first course is called Machine Learning Foundations. It’s designed to be:
Beginner-first — written like I’m teaching a smart friend
Practical — you work with real datasets, in notebooks
Builder-oriented — you build a working prediction system from scratch
100% free
Everything is written from scratch (no scraped MOOCs), and designed to be intuitive, visual, and incremental. If you've been curious about ML but got turned off by linear algebra walls or half-baked tutorials, this might help.
Would love your feedback — especially from non-ML devs or curious builders trying to learn.
After months of building, I’m excited to share Halgorithm — a free, hands-on course platform to help anyone get started with machine learning (even without a math or CS background).
The goal is to fix what I felt was missing in many intro ML resources:
Too much theory, not enough doing
Overloaded with math, too little intuition
Toy datasets, no real-world messiness
The first course is called Machine Learning Foundations. It’s designed to be:
Beginner-first — written like I’m teaching a smart friend
Practical — you work with real datasets, in notebooks
Builder-oriented — you build a working prediction system from scratch
100% free
Everything is written from scratch (no scraped MOOCs), and designed to be intuitive, visual, and incremental. If you've been curious about ML but got turned off by linear algebra walls or half-baked tutorials, this might help.
Would love your feedback — especially from non-ML devs or curious builders trying to learn.
Thanks!