Interactive Demo
BPTT Visualizer
BPTT Visualizer is a free, interactive learning demo from the Backpropagation course on Lykke. It helps you build intuition for Backpropagation through time (BPTT), Backpropagation through structure (BPTS), Recurrent Neural Networks (RNN), Network Unfolding. Play with it directly in your browser — it features 3 sliders and 2 buttons. Click "Run Backprop" to see the error signal flow through time. This demo lives in the “Backpropagation for Specialized Architectures” section of the course.
How to use this demo
- Click "Run Backprop" to see the error signal flow through time.
- Drag the “Time Steps (Unfolding)”, “Weight (W)” sliders to change the inputs and watch the result update live.
- Use the “Run Backprop”, “Reset” buttons to trigger actions or reset the demo.
- Experiment freely — there's nothing to break, and every change is reversible.
What you'll explore
- Backpropagation through time (BPTT)
- Backpropagation through structure (BPTS)
- Recurrent Neural Networks (RNN)
- Network Unfolding
Frequently asked questions
What does the BPTT Visualizer demo do?
How backpropagation is adapted for sequential and recursive data structures. BPTT Visualizer turns that idea into something you can manipulate directly and watch respond.
What Backpropagation concept does BPTT Visualizer teach?
How backpropagation is adapted for sequential and recursive data structures. It focuses on Backpropagation through time (BPTT), Backpropagation through structure (BPTS), Recurrent Neural Networks (RNN), Network Unfolding from the “Backpropagation for Specialized Architectures” section.
What can I control in BPTT Visualizer?
The “Time Steps (Unfolding)”, “Weight (W)” sliders change the key inputs; the “Run Backprop”, “Reset” buttons run actions or reset the demo. Every change updates the visualization in real time, so you can see exactly how each variable affects the outcome.
How does BPTT Visualizer fit into the Backpropagation course?
This course provides a comprehensive exploration of Backpropagation, the fundamental algorithm for training neural networks. It covers the historical evolution of the method from its roots in sensitivity analysis and op… This demo is the interactive piece for the “Backpropagation for Specialized Architectures” section. Open the full Backpropagation course wiki at https://www.getlykke.com/explore/public/backpropagation-d2b74f25-f27c-4873-a2c7-bead22dc4b22 for notes, flashcards, quizzes and the other demos.
What will I understand better after using BPTT Visualizer?
You'll build intuition for Backpropagation through time (BPTT), Backpropagation through structure (BPTS), Recurrent Neural Networks (RNN), Network Unfolding — and, crucially, see how they behave when you change the inputs, which is hard to get from a textbook or lecture on Backpropagation alone.
From the Backpropagation course
This interactive demo is part of the Backpropagation for Specialized Architectures section. Explore the full Backpropagation course wiki on Lykke — with notes, flashcards, quizzes and more interactive demos.
Open the Backpropagation course →