What does "Neural Network" mean?

A Neural Network is a computational model inspired by the human brain’s structure and function. It consists of interconnected nodes (neurons) organized in layers. Each neuron processes input signals, applies weights, and produces an output that influences subsequent neurons.

Use Cases

Image Recognition:

Classifying objects in images based on learned features.

Cognitive Speech Recognition:

Transcribing spoken language into text.

Financial Forecasting:

Predicting stock prices based on historical data.

Importance

Complex Pattern Recognition:

Capable of learning and recognizing intricate patterns in data.

Adaptability:

Adjusts weights and biases during training to optimize performance.

Scalability:

Scales well with large datasets and complex problems in various domains

Analogies

A Neural Network is like a team of specialists working together to solve a complex puzzle. Each specialist (neuron) focuses on a specific aspect of the puzzle, and their collective efforts (layers of neurons) contribute to solving the puzzle efficiently based on their learned experiences.

Where can you find this term?

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