Introduction to Neural Networks

Artificial Intelligence & Machine Learning Basics 215 views Nov 05, 2025 1 min read

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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