Machine learning: computers learning and making predictions without explicit programming using data-driven algorithms.
Training models using labeled examples, with algorithms like linear regression, decision trees, and support vector machines.
Unlabeled data is explored to find meaningful insights and groupings. Clustering algorithms like K-means and hierarchical clustering are commonly used.
Agents learn from feedback received through interaction with an environment, maximizing rewards by finding optimal policies.
Interconnected nodes, called neurons, process data in layers. Deep neural networks excel in image recognition and natural language processing.
Machines analyze visual data using techniques like object detection and image classification with convolutional neural networks.
This research paper explores how machine learning can detect and mitigate attacks in IoT environments by analyzing network traffic patterns and anomalies.