Definition:
A Neural Network is a computational model inspired by the human brain, used in machine learning and deep learning to recognize patterns and make predictions.
Key Points:
Composed of neurons (nodes) arranged in layers:
Input Layer: Receives data
Hidden Layer(s): Processes data
Output Layer: Produces results
Uses weights and activation functions to learn patterns
Learns from data through training and backpropagation
Applications:
Image and speech recognition
Natural Language Processing (NLP)
Self-driving cars
Advantages:
Can model complex non-linear relationships
Powerful for large datasets
Limitations:
Requires large amounts of data
Computationally intensive
Difficult to interpret
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