The toolkit for those who want to learn about artificial intelligence without coding
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Titanic : simple data for classification according to categories and numbers
Iris : simple data for classification according to categories and numbers
Boston Housing : simple data for regression according to categories and numbers
Mnist: 60,000 28x28 images (digits) for simple tests (generation or classification)
FashionMnist: 10,000 28x28 images (clothes) for simple tests (generation or classification)
CelebA: 60,000+ larger and color images (generation)
Cifar-10: small color images in 10 categories (classification)
Flickr8k: small color images associated with text (text 2 image, image 2 text)
Children's Stories: 250 children's stories in English to begin with text generation
French cooking recipes
English poems (generation)
French news (generation)
Movie Reviews (in English): Classification
English news with 4 categories (classification)
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classification model trained with the Titanic dataset
regression model trained with the Boston Housing dataset
image classification model trained with the fashion mnist dataset
auto encoder model trained with the fashion mnist dataset
auto encoder model trained with the celebA dataset
variational auto encoder (VAE) model trained with the fashion mnist dataset
variational auto encoder (VAE) trained with the celebA dataset
decoder (VAE) trained with the fashion mnist dataset
decoder (VAE) trained with the celebA dataset
diffusion model trained with the fashion mnist dataset
diffusion model trained with the celebA dataset (with EMA)
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