Build · Grades 9-12
Neural Network Playground
Add layers, tweak weights, and visualize how a network learns.
The AI idea behind it
A neural network passes numbers through layers of artificial neurons. Every connection has a weight, and each neuron adds up its weighted inputs and passes the result on. The network's answer is whatever comes out of the last layer.
Training means adjusting the weights so the answers get less wrong, a little at a time. More layers let a network learn more complicated patterns, but they also make it slower to train and easier to overfit.
How it works in the app
- Add or remove layers and neurons to change the shape of the network.
- Change weights by hand and see how the output responds.
- Train the network and watch how its predictions change as it learns.
Try this
The smallest network that works
- Start with the fewest layers and neurons the tool allows. Train it and note how well it does.
- Add one layer, train again and record the change. Repeat a few times.
- Find the point where adding more stops helping, and explain why bigger is not always better.
What it shows: Network size is a trade-off. Engineers pick the smallest network that solves the problem, because extra capacity costs time and can memorise noise.
Where it fits in the curriculum
More Build tools
Decision Tree BuilderDesign decision trees from scratch and watch them classify data in real time.
Chatbot BuilderTrain a rule-based chatbot and see how intent and response design works.
Recommendation EngineBuild a cosine-similarity recommender and see how Netflix and Spotify choose what to show you next.
Try Neural Network Playground in the app
One of the creation tools in LittleAIMaster for Grades 6-12.