Failed-ML VS BetaML.jl

Compare Failed-ML vs BetaML.jl and see what are their differences.

Failed-ML

Compilation of high-profile real-world examples of failed machine learning projects (by kennethleungty)
AI Artificial intelligence Data Science Deep Learning Machine Learning ML failed-ml Computer Vision data-engineering data-quality Natural Language Processing Production recsys failed-machine-learning failed-data-science Regression Forecasting Classification fml
Source Code
towardsdatascience.com
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BetaML.jl

Beta Machine Learning Toolkit (by sylvaticus)
Machine Learning neural-networks Clustering Data Science Deep Learning imputation Regression Classification decision-trees Julia Pca random-forest AI Artificial intelligence ML
Source Code
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Failed-ML BetaML.jl
1 1
691 90
- -
5.2 8.1
8 days ago 6 days ago
Julia
MIT License 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.

Failed-ML

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

BetaML.jl

Posts with mentions or reviews of BetaML.jl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-02.

What are some alternatives?

When comparing Failed-ML and BetaML.jl you can also consider the following projects:

ML-YouTube-Courses - 📺 Discover the latest machine learning / AI courses on YouTube.

MLJ.jl - A Julia machine learning framework

squirrel-core - A Python library that enables ML teams to share, load, and transform data in a collaborative, flexible, and efficient way :chestnut:

Lux.jl - Explicitly Parameterized Neural Networks in Julia

yt-channels-DS-AI-ML-CS - A comprehensive list of 180+ YouTube Channels for Data Science, Data Engineering, Machine Learning, Deep learning, Computer Science, programming, software engineering, etc.

NaiveNASlib.jl - Relentless mutation!!

AI-Conference-Info - Extensive acceptance rates and information of main AI conferences

classifai - Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence.

RubixML - A high-level machine learning and deep learning library for the PHP language.

applied-ml - 📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

LIBSVM.jl - LIBSVM bindings for Julia

Failed-ML vs ML-YouTube-Courses BetaML.jl vs MLJ.jl Failed-ML vs squirrel-core BetaML.jl vs Lux.jl Failed-ML vs yt-channels-DS-AI-ML-CS BetaML.jl vs NaiveNASlib.jl Failed-ML vs AI-Conference-Info BetaML.jl vs classifai Failed-ML vs RubixML BetaML.jl vs RubixML Failed-ML vs applied-ml BetaML.jl vs LIBSVM.jl