lorenzoh

DataLoaders.jl. A parallel iterator for large machine learning datasets that don't fit into memory inspired by PyTorch's `DataLoader` class.

Pollen.jl. Format-independent document generation tool built for interactive work

Invariants.jl. Julia package for creating composable invariants with helpful error messages

PyTorchTraining.jl. Prototype for using PyTorch models in FluxTraining.jl

DLPipelines.jl. Interfaces for deep learning data pipelines.

pollenjl-frontend. The Svelte frontend for Pollen.jl

FeatureRegistries.jl. Registries for package feature for easy discovery.

DLDatasets.jl. Quickly load datasets for deep learning.

PyNNTraining.jl. Use FluxTraining.jl to train neural networks in Python frameworks

sudoku-scanner. A scanner that detects, recognizes and solves sudoku puzzles from real-life pictures using a pipeline of classical Computer Vision algorithms.

FluxModels.jl. Some useful model definitions from recent papers, mostly for computer vision.

TestTUI.jl. A little TUI that continuously runs tests for your in-development packages.

dbopendata8. Project from DB OpenData Hackathon 12/16/17

DeepLearningInJulia. Tutorials for deep learning in Julia

InvariantsCore.jl. Core package for Invariants.jl

lambda-packager. Uses the amazonlinux Docker image to build Python packages for AWS Lambda

FastTimm.jl. Julia

ModelUtils.jl. Utilities for working with Flux models. Initialization, hooks, iteration, visualization and more...

PollenExample.jl. Julia

fu-enrollments. Python

VisionDatasets.jl. Download and load common computer vision datasets for different tasks

publish-theme. A theme for Publish.jl

softwareproject-codingixd. JavaScript