Visual lessons and practice
Learn the math behind
machine learning
Work through the mathematics behind machine learning with diagrams and step-by-step examples, then test your understanding with practice questions.
Choose a starting point based on what you already know.
How the dot product compares vectors
A dot product connects coordinates to geometry.
Explore the subjects
From vectors to training a model
Lessons connect through prerequisites, so you can find the background you need before tackling a new concept.
Foundations
Read equations with confidence.
Get comfortable with the language of mathematics: numbers, algebra, functions, and graphs.
Explore subjectLinear algebra
See the structure in your data.
Understand vectors, matrices, and the geometry behind data and its transformations.
Explore subjectCalculus
Understand how a model changes.
Explore change, gradients, and the chain rule that makes learning algorithms possible.
Explore subjectProbability
Reason about uncertain outcomes.
Work with uncertainty, distributions, and the evidence that changes what you believe.
Explore subjectStatistics
Learn what your data can tell you.
Move from observations to estimates, inference, regression, and model evaluation.
Explore subjectOptimization
Understand how models learn.
Follow the steps that improve a model, from gradient descent to regularization.
Explore subjectHow you learn
Build understanding
through practice
- 01
Make the idea concrete
Follow a worked example alongside a diagram that shows what the equation describes.
- 02
Find out what you understand
Predict an outcome and work through a question. Feedback helps you see where your reasoning holds and where to look again.
- 03
Revisit what you have learned
Return to ideas through continuing practice and review, then build on them in the next lesson.
The Glacius Blog
A closer look at the mathematics
Read worked explanations of the questions that come up while learning mathematics and machine learning.