Overview#

Weight

Weight in Artificial Neural networks#

Weight is the number of units in next layer × number of units in the previous layer is the and is the weight matrix where the value of the superscript indicates the layer.

Typically Weight is represented as "w"

More Information#

There might be more information for this subject on one of the following:

• Artificial Neural network
• Artificial Neuron
• Backpropagation
• Cost function
• Dropout Regularization
• Forward propagation
• Hidden layer
• Logistic Regression
• Machine Learning Taxonomy
• Output layer
• Output node
• Regularization
• Sigmoid neuron
• Synapses