In TensorFlow Playground, a blue line between neurons indicates that the connection has a positive weight. This visualization allows users to understand how different weights impact the output of a neural network.
When a connection between neurons is assigned a positive weight, it means that the output of the preceding neuron will positively influence the activation of the following neuron. This is a key concept in neural networks as it directly affects how data is propagated through the layers, ultimately influencing the model's predictions.
Understanding the color coding is essential for visualizing the behavior of the network. A blue connection signifies that increasing the output of the upstream neuron will enhance the activity of the downstream neuron, playing a critical role in how the model learns from the data. This feedback mechanism is fundamental to training neural networks, as it allows for the adjustment of weights based on the results of previous epochs.