AutoMLPipeline.jl
maptrace
AutoMLPipeline.jl | maptrace | |
---|---|---|
1 | 1 | |
350 | 123 | |
1.4% | - | |
5.5 | 0.0 | |
5 days ago | over 2 years ago | |
HTML | Python | |
MIT License | GNU General Public License v3.0 or later |
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AutoMLPipeline.jl
maptrace
-
MlJ.jl: A Julia Machine Learning Framework
How far could you go with some automatic cleaning, something like `maptrace` [0] and some topology rules when you have your vector file to finish with some manual artistic polish? Because, i don't believe that you will achieve easily the "do-it-like-me" result expected from either GAN or VAE or autoencoders. In case of you want to look, the classic examples about style transfer (Photo to Van Gogh style, etc.) seems to be the way to go. Specific to Julia, you can look at Flux.jl or KNet.jl.
[0] https://github.com/mzucker/maptrace
What are some alternatives?
MLJ.jl - A Julia machine learning framework
Pkg.jl - Pkg - Package manager for the Julia programming language
ScientificTypes.jl - An API for dispatching on the "scientific" type of data instead of the machine type
unity-ml-agents-turret-defense - A reinforcement learning agent playing as the turret, where its goal is to allow ten friendly units to enter the base, and loses if an enemy unit has entered the base or if two friendly units were shot.
GCP-DevOpsPipelineContinuousIntegration-Deployment - Build a continuous integration pipeline using Cloud Source Repositories, Cloud Build, build triggers, and Container Registry. Deploy applications to the Google Cloud services App Engine, Kubernetes Engine, and Cloud Run.
seq-pipeline - Workspace for data science projects and NGS pipelines. Contains RStudio, Jupyter Notebook, VSCode and file manager. Can connect to Tailscale network to bypass firewalls.