NaiveGAflux.jl
Evolve Flux networks from scratch! (by DrChainsaw)
model-zoo
Please do not feed the models (by FluxML)
NaiveGAflux.jl | model-zoo | |
---|---|---|
2 | 5 | |
41 | 885 | |
- | 0.6% | |
7.3 | 4.6 | |
5 months ago | about 2 months ago | |
Julia | Julia | |
MIT License | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
NaiveGAflux.jl
Posts with mentions or reviews of NaiveGAflux.jl.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-01-08.
-
Neural Architecture Search (NAS) [D]
Fwiw (and shameless plug disclaimer), I made a library for easily toying around with evolution based NAS. It uses mixed integer programming to align the neurons (e.g. when resizing a layer) which it gives much higher degrees of freedom over what architectures one can allow in the search space over anything else I have seen: https://github.com/DrChainsaw/NaiveGAflux.jl
-
[P] NAS repos
Maybe not exactly what you are looking for, but: https://github.com/DrChainsaw/NaiveGAflux.jl
model-zoo
Posts with mentions or reviews of model-zoo.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-08-12.
- sci-kit learn best for machine learning with Julia?
-
Are there anyway to translate IPA to English? atleast, IPA text to pronounce sound
If your task is limited to isolated words or words that are separated by spaces, you can reverse the [CMU Pronouncing Dictionary](www.speech.cs.cmu.edu/cgi-bin/cmudict). In a programmatic environment with a dictionary/hash map, you will need to have the values be an extensible list of some sort to account for homophones. You could also train an ML model to convert phonemes to graphemes, like reversing this neural network model.
-
Project in julia
You can also do some deep learning in Julia if you like. Flux.jl is Julia's deep learning library, and they have a model zoo of easy to follow working examples as a good starting point.
-
Simple neural network model in Flux.jl doesn't seem to update the loss function
Secondly, flux.train! computes epochs automatically and is designed to take the entire data set. If you want to use the DataLoader, I think you probably need to write a custom training loop. It's not that complicated thankfully. The model zoo has some nice examples like: https://github.com/FluxML/model-zoo/blob/master/vision/mlp_mnist/mlp_mnist.jl
-
Any Machine Learning Projects to Make with Julia
Check out the Flux.jl model zoo: https://github.com/FluxML/model-zoo#examples-listing
What are some alternatives?
When comparing NaiveGAflux.jl and model-zoo you can also consider the following projects:
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
GeneticAlgorithmPython - Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
Transformers.jl - Julia Implementation of Transformer models
TorchGA - Train PyTorch Models using the Genetic Algorithm with PyGAD
AlphaZero.jl - A generic, simple and fast implementation of Deepmind's AlphaZero algorithm.
reproduced_data
NaiveNASlib.jl - Relentless mutation!!
FastAI.jl - Repository of best practices for deep learning in Julia, inspired by fastai