Explore Generative Adversarial Networks directly in the browser with GAN Lab. There are many cool features that support interactive experimentation.
- Interactive hyperparameter adjustment
- User-defined data distribution
- Slow-motion mode
- Manual step-by-step execution
ConvNet Playground is an interactive visualization tool for exploring Convolutional Neural Networks applied to the task of semantic image search.
Feature inversion to visualize millions of activations from an image classification network leads to an explorable activation atlas of features the network has learned. This can reveal how the network typically represents some concepts.
Available in many different languages.
New to Deep Learning? Tinker with a Neural Network in your browser.
Initialization can have a significant impact on convergence in training deep neural networks. Simple initialization schemes can accelerate training, but they require care to avoid common pitfalls. In this post, deeplearning.ai folks explain how to initialize neural network parameters effectively.
It's increaingly important to understand how data is being interpreted by machine learning models. To translate the things we understand naturally (e.g. words, sounds, or videos) to a form that the algorithms can process, we often use embeddings, a mathematical vector representation that captures different facets (dimensions) of the data. In this interactive, you can explore multiple different algorithms (PCA, t-SNE, UMAP) for exploring these embeddings in your browser.
A visual introduction to probability and statistics.
The best way to understand a neural network is to code it up from scratch!
