Artificial Intelligence
How Machines Learn: Core Concepts Without the Math
How Machines Learn: Core Concepts Without the Math is a course in AI & Machine Learning Mastery: From Zero to Practitioner. 10 lessons covering How Machines Actually Learn — The Core Idea Behind Every Algorithm; Gradient Descent — How Models Find the Best Answer; Decision Trees — Making Predictions by Asking Questions.
10 published lessons · Online learning · Part of Learn & Grow
View the curriculum here. Sign in to access lessons under your learning plan.
What this course covers
- How Machines Actually Learn — The Core Idea Behind Every Algorithm · 13 min
- Gradient Descent — How Models Find the Best Answer · 13 min
- Decision Trees — Making Predictions by Asking Questions · 12 min
- Random Forests — Why Many Weak Models Beat One Strong Model · 13 min
- The Bias-Variance Tradeoff — The Most Important Balance in ML · 14 min
- Cross-Validation — Getting Reliable Performance Estimates · 12 min
- Regularisation — Preventing Overfitting Without Losing Power · 13 min
- Hyperparameter Tuning — Finding the Best Settings for Your Model · 13 min
- Ensemble Methods — Boosting and Stacking · 14 min
- Feature Engineering — Turning Raw Data Into Model Intelligence · 15 min
Continue your learning path
This course belongs to AI & Machine Learning Mastery: From Zero to Practitioner. Explore the full academy to see the other courses in this learning path.
How to get started
- Create your Learn & Grow account or sign in.
- Review the available access plans and choose the academy you need.
- Work through the lessons and activities in your learning dashboard.
Contact support if you need help choosing the right learning path.