BSIT - 1B (Fill in the blank)

______________ learning involves learning from labeled data (input-output pairs).

______________ machines (SVMs) find an optimal hyperplane that maximally separates data points of different classes.

______________ networks are complex models inspired by the human brain, composed of interconnected layers of nodes (neurons). They are excellent for complex tasks like

______________ learning involves learning from unlabeled data, discovering patterns and structures.

______________ reduction is an unsupervised learning technique that reduces the number of features in a dataset while preserving important information. An example is Principal Component Analysis (PCA).

______________ Decision Processes (MDPs) are a mathematical framework for modeling decision-making in situations where outcomes are uncertain and are often used to formulate reinforcement learning problems.

In robotics, machine learning is used for ______________ recognition, which involves using computer vision and machine learning to identify objects in the robot's environment.

In robotics, ______________ planning involves planning a path for the robot to move from one location to another, avoiding obstacles.

The key difference between supervised and unsupervised learning is the presence of ______________ in the data.

______________ learning is a different paradigm altogether, focusing on learning through interaction and feedback (rewards).