Interactive Neural Classifier (Real-Time Backprop)
2D Decision Boundary Space
Decision Boundary & Data
Loss & Convergence Curve
0
Epochs
0.693
BCE Loss
50.0%
Accuracy
0.05
Learning Rate
Curriculum Roadmap & Exportable Code
Stage 3: Deep Learning
1. Math FoundationsVectors & Calculus
Linear algebra (matrix mult, eigenvalues), Multivariate calculus (gradients, chain rule), and Probability distributions.
2. Classical Machine Learningscikit-learn
Linear/Logistic Regression, Decision Trees, Random Forests, SVMs, and PCA dimensionality reduction.
3. Deep Neural NetworksPyTorch Sandbox
Backpropagation, Multi-Layer Perceptrons, loss functions (BCE/MSE), and non-linear decision boundary mapping.
4. Modern AI & TransformersLLM Architectures
Self-Attention, Transformer encoders/decoders, fine-tuning (LoRA), embeddings, and Retrieval-Augmented Generation.