The output layer is the final layer in a neural network that produces the result of the network's computation, translating the network's internal representations into actionable outcomes. It determines the network's predictions or classifications and is crucial for tasks such as regression, classification, and decision-making.

Output Layer

output layer

final layer

A neural network is a computational model inspired by the human brain's network of neurons, designed to recognize patterns and solve complex problems through learning from data. It consists of layers of interconnected nodes that adjust their weights based on input data to improve accuracy over time.

neural network

result of the network's computation

internal representations

actionable outcomes

network's predictions

classifications

tasks such as regression

Classification is a supervised learning approach in machine learning where the goal is to predict the categorical label of a given input based on training data. It is widely used in applications such as spam detection, image recognition, and medical diagnosis, where the output is discrete and predefined.

classification

Decision-making is a cognitive process that involves selecting a course of action from multiple alternatives, often under conditions of uncertainty. It is influenced by various factors such as individual biases, available information, and the decision-making environment.

CUSTOMIZE YOUR LEARNING

CUSTOMIZE YOUR LEARNING

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