Machine Learning
Computer ScienceChapter 1 — Introduction to Machine Learning
Lesson 1.5 : Types of Machine Learning
Reading & Interactive Lesson
Types of Machine Learning
Reading Material & Notes
Types of Machine Learning
Machine Learning can be broadly categorized according to how the learning system receives and uses data.
1. Supervised Learning
In supervised learning, the model is trained using data that contains known output values.
Examples include classification and regression.
2. Unsupervised Learning
In unsupervised learning, the data does not contain predefined output labels. The algorithm attempts to discover patterns or groups in the data.
Clustering is a common example.
3. Semi-Supervised Learning
Semi-supervised learning uses a combination of labeled and unlabeled data.
4. Reinforcement Learning
In reinforcement learning, an agent learns by interacting with an environment and receiving rewards or penalties.
| Type | Learning Data | Example |
|---|---|---|
| Supervised | Labeled | House price prediction |
| Unsupervised | Unlabeled | Customer clustering |
| Semi-Supervised | Labeled + Unlabeled | Image classification |
| Reinforcement | Rewards/Penalties | Game-playing agent |
Course Curriculum
10 Chapters • 50 Lessons
Chapter 1 — Introduction to Machine Learning
5 Lessons
Chapter 2 — Types of Machine Learning
5 Lessons
Chapter 3 — Python for Machine Learning
5 Lessons
Chapter 4 — Data Preprocessing
5 Lessons
Chapter 5 — Regression Algorithms
5 Lessons
Chapter 6 — Classification Algorithms
5 Lessons
Chapter 7 — Clustering Algorithms
5 Lessons
Chapter 8 — Model Evaluation
5 Lessons
Chapter 9 — Feature Engineering and Model Improvement
5 Lessons
Chapter 10 — Machine Learning Projects
5 Lessons