All Katas - ML Katas

Implement a Neural Ordinary Differential Equation

yesterday hard (<30 mins) | pytorch generative neural ode dynamics

### Description Instead of modeling a function directly, a Neural ODE models its derivative with a neural network. The output is then found by integrating this derivative over time. [1] Your task...

Differentiable Additive Synthesizer

yesterday medium (<30 mins) | pytorch generative ddsp audio

### Description Differentiable Digital Signal Processing (DDSP) is a technique that combines classic signal processing with deep learning by making the parameters of synthesizers learnable via...

Neural Cellular Automata (NCA) Update Step

yesterday hard (<30 mins) | pytorch generative nca alife complex systems

### Description Neural Cellular Automata (NCA) are a fascinating generative model where complex global patterns emerge from simple, local rules learned by a neural network. [1] A grid of "cells,"...

Normalizing Flow for Density Estimation

yesterday hard (<30 mins) | pytorch generative normalizing flow

### Description Implement a simple 2D Normalizing Flow model. Normalizing Flows transform a simple base distribution (like a Gaussian) into a more complex distribution by applying a sequence of...

Custom `DataLoader` for On-the-Fly Image Generation

this month medium (<30 mins) | dataset dataloader custom generative synthetic

Create a **custom `torch.utils.data.Dataset`** that doesn't load data from disk. Instead, the `__getitem__` method should **generate** an image on the fly (e.g., a simple geometric shape, a random...

Training a Variational Autoencoder (VAE)

this month hard (>1 hr) | loss vae autoencoder generative kl

Implement and train a **Variational Autoencoder (VAE)** on a dataset like MNIST. The encoder should map the input to a latent space distribution (mean and variance), and the decoder should...

Generative Adversarial Network (GAN) on MNIST

this month hard (>1 hr) | training adversarial generative mnist gan

Implement and train a simple **Generative Adversarial Network (GAN)**. The network consists of a generator and a discriminator. The generator takes a random noise vector and tries to generate a...

Implementing a Simple VAE for Text (Sentence VAE)

this month hard (>1 hr) | rnn vae generative text nlp

Implement a **Variational Autoencoder (VAE)** for text, often called a Sentence VAE. The encoder will be an RNN (e.g., GRU) that outputs a latent distribution, and the decoder will be another RNN...