$N
Epoch

Data

Which dataset do you want to use?

Features

What properties do you want to include?

Click anywhere to edit.
Weight/Bias is 0.2.
Hover to see it larger—this is the output from one $N.
The thickness of the lines, representing varying weights, illustrates how the outputs are mixed.

Output

Test loss
Training loss
Data, neuron values, and weight values are represented by colors.

Element Meanings:

Color Scheme:

  • Blue: Positive values/influence
  • Orange: Negative values/influence

Data Points (Small Circles):

  • Blue circles: +1
  • Orange circles: -1

Connection Lines:

  • Blue lines: Preserving neuron output
  • Orange lines: Diminishing neuron output

Output Layer:

  • Maintains original color coding of data points

Background:

  • Color type: Prediction result
  • Color intensity: Prediction confidence level

What Do All the Colors Mean?

Neural networks are a cutting-edge computational method inspired by the workings of the human brain. These systems mimic the way biological neurons process information, enabling computers to learn patterns and make predictions.

At their core, neural networks consist of interconnected software "neurons" that exchange information. These neurons work together to process input data, passing it through layers of the network to generate meaningful outputs.

Through repeated attempts to solve a specific problem, the network adapts over time. Connections that lead to successful results are strengthened, while those associated with failures are weakened, allowing the system to improve its performance dynamically.

For those interested in learning more, Michael Nielsen's Neural Networks and Deep Learning offers an excellent introduction. For readers seeking a more detailed technical understanding, Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville is highly recommended.

Why We Chose the BSC

This is the first neural network visualization project built on BSC, designed to attract users interested in AI and memes to join our community. We reward users with the $N token and will also use $N to incentivize the development of more AI visualization projects on BSC.

Additionally, we plan to continue development, with more neural network-related projects to be updated on this platform.

We believe that current trends show a strong synergy between AI applications and memes on the BSC blockchain. Our goal is to introduce more AI foundational concepts into the BSC ecosystem.