What is a Neural Network?
Introduction
Imagine that you want to learn how to translate text from English into Spanish. You learn languages by memorizing words and phrases, their meanings, and the context in which they are used. Based on this experience, you will be able to translate new texts that you have never seen before.
Another case is the classification of cats and dogs. Just as a person learns to distinguish them from examples seen in life, so a neural network can learn to distinguish them from such examples.
A neural network functions in a similar way β it learns from examples, which can include texts, images, sounds, or any other type of data it is designed to process. Just as a person learns a language by recognizing patterns, a neural network identifies structures and relationships within the data.
Using these patterns, it can perform tasks such as classification (determining the category of an object), regression (predicting numerical values like house prices), or generation (creating new content based on learned patterns). The process of training a neural network on labeled examples is known as supervised learning, which is the most common training approach.
Training a neural network involves teaching it using examples that already have known answers, referred to as labeled examples. It is similar to giving a quiz where the correct answers are already provided, allowing the model to learn from these examples.
When the network is asked to make predictions, it receives new examples without known answers β these inputs are unlabeled. The model then applies what it has learned during training to predict the correct outcomes on its own.
Neural Network Example
This is a demonstration of a Neural Network specifically designed to identify drawings of cats and dogs.
It tackles a classification problem by processing an input from an initially unknown class and outputting the identified class.
Try using it to get a deeper understanding.
- LMB (left mouse button) - to draw;
- Shift + LMB - to erase.
Thanks for your feedback!
Ask AI
Ask AI
Ask anything or try one of the suggested questions to begin our chat
Awesome!
Completion rate improved to 4What is a Neural Network?
Swipe to show menu
Introduction
Imagine that you want to learn how to translate text from English into Spanish. You learn languages by memorizing words and phrases, their meanings, and the context in which they are used. Based on this experience, you will be able to translate new texts that you have never seen before.
Another case is the classification of cats and dogs. Just as a person learns to distinguish them from examples seen in life, so a neural network can learn to distinguish them from such examples.
A neural network functions in a similar way β it learns from examples, which can include texts, images, sounds, or any other type of data it is designed to process. Just as a person learns a language by recognizing patterns, a neural network identifies structures and relationships within the data.
Using these patterns, it can perform tasks such as classification (determining the category of an object), regression (predicting numerical values like house prices), or generation (creating new content based on learned patterns). The process of training a neural network on labeled examples is known as supervised learning, which is the most common training approach.
Training a neural network involves teaching it using examples that already have known answers, referred to as labeled examples. It is similar to giving a quiz where the correct answers are already provided, allowing the model to learn from these examples.
When the network is asked to make predictions, it receives new examples without known answers β these inputs are unlabeled. The model then applies what it has learned during training to predict the correct outcomes on its own.
Neural Network Example
This is a demonstration of a Neural Network specifically designed to identify drawings of cats and dogs.
It tackles a classification problem by processing an input from an initially unknown class and outputting the identified class.
Try using it to get a deeper understanding.
- LMB (left mouse button) - to draw;
- Shift + LMB - to erase.
Thanks for your feedback!
