Interactive Sequence Modeling
Understand the Architectures of Time.
The definitive, interactive guide to Recurrent Neural Networks, LSTMs, and GRUs. Stop reading static equations—start visualizing data flow.
LSTM Gated Architecture
Memory Cells & Hidden Projections
Cₜ₋₁
hₜ₋₁
xₜ
σ
σ
tanh
σ
⊗
⊗
⊕
tanh
⊗
Cₜ
Wᵧ
yₜ
Inputs Arrive
Gathering xₜ, hₜ₋₁, and Cₜ₋₁
Live unrolling of an LSTM Cell: Monitoring gate activity and cell state persistence.
Rigorous Theory
Every gate explained through first principles, from vanishing gradients to Gated Recurrent Units.
Live Visuals
Interactive components built with Framer Motion that let you unroll networks step-by-step.
Production Ready
Implementation guides for PyTorch and TensorFlow, optimized for real-world sequential data.