What are the four primary types of machine learning in the module?
Supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning
Explanation
The four main types of Machine Learning are:
Supervised Learning – Learns from labeled data to make predictions.
Example: Email spam detection, house price prediction.
Unsupervised Learning – Finds patterns or groups in unlabeled data.
Example: Customer segmentation, anomaly detection.
Semi-Supervised Learning – Uses a small amount of labeled data along with a large amount of unlabeled data.
Example: Image classification with limited labeled images.
Reinforcement Learning – Learns by interacting with an environment and receiving rewards or penalties.
Example: Self-driving cars, robotics, game-playing AI.
Option Review
a) Supervised learning, unsupervised learning, semi-supervised learning, reinforcement learning
b) Decision tree, K-means clustering, logistic regression, naive Bayes These are algorithms, not learning types.
c) Data preprocessing, model training, evaluation, deployment. These are stages of the ML workflow.
d) Deep learning, neural networks, linear regression, SVM. These are models or techniques, not the four main learning paradigms.
