orion VS ds2ai-python

Compare orion vs ds2ai-python and see what are their differences.

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orion ds2ai-python
1 1
280 10
0.4% -
7.4 0.0
5 months ago over 1 year ago
Python Python
GNU General Public License v3.0 or later Apache License 2.0
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.

orion

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

ds2ai-python

Posts with mentions or reviews of ds2ai-python. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing orion and ds2ai-python you can also consider the following projects:

nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

autoai - Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.

dreamerv2 - Mastering Atari with Discrete World Models

SAP-HANA-AutoML - Python Automated Machine Learning library for tabular data.

aimet - AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

pytorch-forecasting - Time series forecasting with PyTorch

nylon - An intelligent, flexible grammar of machine learning.

Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

awesome-experimental-standards-deep-learning - Repository collecting resources and best practices to improve experimental rigour in deep learning research.

H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

asreview - Active learning for systematic reviews