CoursesMachine Learning Basics
IntermediateMachine LearningFundamentals
Machine Learning Basics
Core ML concepts.
8h6 lessons12,340 students4.8
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6
Lessons
Intermediate
Level
Overview
Supervised, unsupervised, training, overfitting.
What you will learn
How ML differs from traditional programming
The three broad families of ML
What 'features' and 'labels' mean
What labelled data is
Classification vs regression
Common algorithms for each
What unsupervised learning is for
Clustering with K-Means
Curriculum
Course content
1
What is ML?
Machine Learning is programming by example instead of by rules.
7 min
2
Supervised Learning
Learning from labelled examples — classification vs regression.
9 min
3
Unsupervised Learning
Finding structure in data that has no labels.
8 min
4
Train / Test Split
Why you must evaluate on data the model has never seen.
8 min
5
Overfitting & Underfitting
The two ways a model fails — and how to fix each.
9 min
6
Evaluation Metrics
Why accuracy can mislead — precision, recall, and the confusion matrix.
9 min