Neural Networks
Definition
A neural network is a type of artificial intelligence model that mimics the functioning of the human brain to process information. It consists of interconnected layers of nodes, or "neurons," that work together to learn from data and make decisions.
Explain Like I'm 5
Imagine you're trying to make a really complicated decision, like what you want for your birthday. You might ask all your friends and family for their suggestions. Each friend is like a neuron in a neural network - they take in information (your question), process it (think about what you might like), and give an output (their suggestion). Just like how you consider all your friends' suggestions to make your final decision, a neural network considers all its neurons' outputs to make its final decision.
Visualization
Graphic Source: Understanding the Structure of Neural Networks
Digging Deeper
Neural networks are inspired by the biological function of neurons in the human brain. They consist of layers: an input layer where data is fed into the network, one or multiple hidden layers where computations are performed, and an output layer where results are produced.
The image illustrates the analogy between a biological neuron and an artificial neuron, showing how inputs are received and processed to produce outputs in both systems.
Each neuron takes inputs, multiplies them by weights (which signify the importance of that particular input), adds them up, applies an activation function (which decides whether that neuron should be activated or not based on the input it received), and passes this output forward.
Training a neural network involves adjusting these weights based on error rates with backpropagation and gradient descent algorithms until it can accurately predict outcomes.
Applications
- Image Recognition: Neural networks can identify objects within images, useful for self-driving cars or medical imaging.
- Natural Language Processing: They can understand human language to enhance communication between humans and machines, such as Siri or Alexa.
- Fraud Detection: Neural networks can recognize patterns to detect fraudulent transactions in banking and finance.
- Stock Market Prediction: They can analyze patterns and trends in financial data to predict future stock prices.
- Healthcare: Neural networks can analyze medical images or patient data to diagnose diseases and predict health outcomes.
Learn More
- Wikipedia link for Neural Network
- Beginner-friendly video on Neural Networks
- In-depth technical resource on Neural Networks