Hypernets VS de-torch

Compare Hypernets vs de-torch and see what are their differences.

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Hypernets de-torch
1 1
261 6
0.8% -
7.7 4.4
8 days ago over 2 years ago
Python Python
Apache License 2.0 MIT License
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.

Hypernets

Posts with mentions or reviews of Hypernets. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-06-28.

de-torch

Posts with mentions or reviews of de-torch. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing Hypernets and de-torch you can also consider the following projects:

aizynthfinder - A tool for retrosynthetic planning

TorchGA - Train PyTorch Models using the Genetic Algorithm with PyGAD

autokeras - AutoML library for deep learning

Sklearn-genetic-opt - ML hyperparameters tuning and features selection, using evolutionary algorithms.

NAS-Projects - Automated deep learning algorithms implemented in PyTorch. [Moved to: https://github.com/D-X-Y/AutoDL-Projects]

FEDOT - Automated modeling and machine learning framework FEDOT

evotorch - Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE.

AgileRL - Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.

nes-torch - Minimal PyTorch Library for Natural Evolution Strategies