Module · Beginner
Getting Started
Three kinds of learning, and the two data distinctions that drive almost every later decision.
- 2 lessons
- 30 min
- 2 simulations
Included in Introduction to Machine Learning· $9
SVM — Classifier and Regressor
Find the boundary with the widest gap to both classes. Simple, and very strong in high dimensions.
- Level
- Intermediate
- Lessons
- 1
- Total time
- 20 min
- Simulations
- 1
Included in Introduction to Machine Learning · $9
Tools you'll use
Python
scikit-learn
pandas
NumPy
Skills
- SVM
- Margins
- Kernel trick
Try it now — free
This is the real simulation from the module. No account needed.
What you will be able to do
- Understand the maximum margin visually
- Tune C and choose a kernel
- Know when an SVM beats the alternatives
Syllabus
1 lesson · 20 minEvery lesson's title and summary is public. The lessons themselves open once you own the track.
Every lesson in Introduction to Machine LearningMargin, C, and Kernels
20 minOne geometric idea, one parameter that sets tolerance, and one trick that lets it curve.
Included with the track Simulation
Lifetime access
$9More in Introduction to Machine Learning
Module · Beginner
Dataset Splitting, Cross-Validation, Data Leakage
Before any algorithm. A bad split produces a beautiful number that lies.
- 2 lessons
- 34 min
- 2 simulations
Included in Introduction to Machine Learning· $9
Module · Beginner
Training, Evaluation, Bias–Variance, Tuning
How to train, how to measure with the right metric, and the one trade-off that explains nearly every model failure.
- 3 lessons
- 48 min
- 3 simulations
Included in Introduction to Machine Learning· $9
Module · Beginner
KNN — Classifier and Regressor
The algorithm that learns nothing, and teaches a great deal precisely because of that.
- 1 lesson
- 16 min
- 1 simulation
Included in Introduction to Machine Learning· $9