MLE-Flashcards VS Failed-ML

Compare MLE-Flashcards vs Failed-ML and see what are their differences.

MLE-Flashcards

200+ detailed flashcards useful for reviewing topics in machine learning, computer vision, and computer science. (by b7leung)
AI Artificial intelligence Computer Vision Machine Learning computer-science Flashcards Interview interview-preparation Review
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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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MLE-Flashcards Failed-ML
4 1
1,860 617
- -
2.7 5.2
almost 2 years ago 2 months ago
GNU General Public License v3.0 only 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.

MLE-Flashcards

Posts with mentions or reviews of MLE-Flashcards. 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 MLE-Flashcards and Failed-ML you can also consider the following projects:

CMU-ECE-CS-Guide - How to survive CMU as an ECE/CS major

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

list-ai-extensions-chrome-addons-firefox - Complete list of AI-powered Extensions for Google Chrome & Addons for Firefox

BetaML.jl - Beta Machine Learning Toolkit

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.

pycm - Multi-class confusion matrix library in Python

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

MLE-Flashcards vs CMU-ECE-CS-Guide Failed-ML vs ML-YouTube-Courses MLE-Flashcards vs list-ai-extensions-chrome-addons-firefox Failed-ML vs BetaML.jl 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