Neural Network Builder
Build a neural network layer by layer, train it on different datasets (XOR, Circle, Spiral), and watch the decision boundary form in real-time. Experiment with architectures, activation functions, and learning rates.
| Layer | Neurons | Activation | Params |
|---|---|---|---|
| Input | 2 | — | 0 |
| Hidden 1 | 6 | relu | 18 |
| Hidden 2 | 4 | relu | 28 |
| Output | 1 | sigmoid | 5 |
| Total Parameters | 51 | ||
Learn Neural Network Builder on DataCamp
Curated courses and career tracks to take your understanding from this demo to real-world mastery. All links open directly on DataCamp.
Introduction to Deep Learning with PyTorch
Build your first neural network with PyTorch. Learn forward pass, backpropagation, activation functions, and gradient descent.
Introduction to TensorFlow in Python
Learn to build neural networks using TensorFlow 2.0. Understand tensors, layers, training loops, and the Keras API.
Introduction to Deep Learning in Python
Master deep learning using Keras. Learn forward and backward propagation, optimization, and regularization techniques.
Intermediate Deep Learning with PyTorch
Advance your PyTorch skills by building CNNs, RNNs, and learning advanced training techniques like batch normalization.
Advanced Deep Learning with Keras
Use the Keras functional API to build multi-output models, siamese networks, and complex architectures beyond sequential models.
Deep Learning in Python
Build expertise in the most popular deep learning frameworks—PyTorch and TensorFlow/Keras—across the full model lifecycle.
