Neural Networks
Definition
Neural Network
Computational models inspired by the human brain that use neurons to learn from data to perform tasks like classification, prediction, and pattern recognition.
NNs are used to:
- Learn and Model Complex and Non-Linear Relationships:
- NNs can capture complex patterns in data that are difficult for traditional algorithms to model.
- They are widely used in fields like image recognition, natural language processing, and autonomous systems.
- Generalize from Initial Inputs:
- NNs can learn from a limited set of examples and apply that knowledge to new, unseen data.
- This ability to generalize makes them powerful for tasks like predictive analytics and recommendation systems.
ANNs are not perfect and can be prone to overfitting (learning the training data too well and failing to generalize to new data).
Theory of KnowledgeHow do ANNs challenge our understanding of intelligence and learning? Can machines truly understand the data they process?
