Machine learning has a steep learning curve but a clear learning path. Here's the most efficient route.

Prerequisites

• Python basics (lists, functions, libraries)
• Basic statistics (mean, variance, distributions)
• Linear algebra intuition (vectors, matrices) — optional for getting started

Fastest Learning Path

1. Google ML Crash Course (free, 15 hours)
2. Kaggle Learn ML courses (free, hands-on)
3. Build 3 projects with scikit-learn on real datasets
4. Fast.ai Practical Deep Learning (if you want neural networks)
5. Kaggle competitions — learn from other people's notebooks

The Most Important Thing

Build projects. Reading without coding is nearly useless in ML.

Reference:

Kaggle Learn

https://www.kaggle.com/learn