Interactive imagesA small network learning as you watch
A small network learning as you watch
A small neural network trains in your browser on the time series or the embeddings of the labelled samples, as you choose, and the window's map is repainted after each epoch beside the loss.
Choose the time series or the embeddings, see the untrained network’s guess, press Start and watch the map take shape, or change the share of samples, the hidden units or the learning rate and train again.
The network trains on the input chosen here.
Loading classification-series-live-window.bin (2.4 MB).
Not trained yet
A change gives a fresh, untrained network.
The loss on the training samples is drawn after each epoch.
- Annual crop
- Cerradão
- Cerrado
- Mangrove
- Natural non-vegetated
- Open cerrado
- Pasture
- Perennial crop
- Silviculture
- Sugarcane
- Water
What to try
- Look at a guess. Before Start the map is marked Untrained: the network’s weights are drawn at random from a seed and nothing has been learned. What does the window look like when every pixel is a guess?
- Watch the first epochs. Press Start and look at the map after one or two epochs. How much of the window has its colours already, and where on the curve does the loss fall fastest?
- Use fewer labels. Set Samples used to 1 % and press Start. The line in the box says how many samples are left for all the classes; compare the map they give with the map from all of them.
- Change the network. Change the hidden units or the learning rate, one at a time, and train again. Which change moves the loss curve most?
- Change the input. Choose the other input above the figure. The map goes back to the untrained guess for that input, and Start trains a fresh network on it with the same settings.