Mathematics-for-ML VS Failed-ML

Compare Mathematics-for-ML vs Failed-ML and see what are their differences.

Mathematics-for-ML

🧮 A collection of resources to learn mathematics for machine learning (by dair-ai)
AI Deep Learning Machine Learning Mathematics ML
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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
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towardsdatascience.com
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Mathematics-for-ML Failed-ML
2 1
4,172 617
2.7% -
0.0 5.2
over 1 year ago 2 months ago
- 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.

Mathematics-for-ML

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

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.

What are some alternatives?

When comparing Mathematics-for-ML and Failed-ML you can also consider the following projects:

Data-Science-Roadmap - Data Science Roadmap from A to Z

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

pycm - Multi-class confusion matrix library in Python

BetaML.jl - Beta Machine Learning Toolkit

ml-blogs-that-are-worth-reading - Blogs on Machine Learning and Deep learning

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

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.

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

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.

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

Mathematics-for-ML vs Data-Science-Roadmap Failed-ML vs ML-YouTube-Courses Mathematics-for-ML vs pycm Failed-ML vs BetaML.jl Mathematics-for-ML vs ml-blogs-that-are-worth-reading Failed-ML vs squirrel-core Failed-ML vs yt-channels-DS-AI-ML-CS Failed-ML vs AI-Conference-Info Failed-ML vs RubixML Failed-ML vs applied-ml Failed-ML vs pycm Failed-ML vs classifai