rtdl VS 100DaysofMLCode

Compare rtdl vs 100DaysofMLCode and see what are their differences.

rtdl

Research on Tabular Deep Learning (Python package & papers) [Moved to: https://github.com/Yura52/rtdl] (by yandex-research)

100DaysofMLCode

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1: (by NishkarshRaj)
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rtdl 100DaysofMLCode
5 1
314 303
- -
8.9 0.0
about 3 years ago over 1 year ago
Python Jupyter Notebook
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.

rtdl

Posts with mentions or reviews of rtdl. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-30.

100DaysofMLCode

Posts with mentions or reviews of 100DaysofMLCode. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing rtdl and 100DaysofMLCode you can also consider the following projects:

ArtLine - A Deep Learning based project for creating line art portraits.

100-Days-Of-ML-Code - 100 Days of ML Coding

tab-transformer-pytorch - Implementation of TabTransformer, attention network for tabular data, in Pytorch

99-ML-Learning-Projects - A list of 99 machine learning projects for anyone interested to learn from coding and building projects

rtdl-num-embeddings - (NeurIPS 2022) On Embeddings for Numerical Features in Tabular Deep Learning

notebooks - Implement, demonstrate, reproduce and extend the results of the Risk articles 'Differential Machine Learning' (2020) and 'PCA with a Difference' (2021) by Huge and Savine, and cover implementation details left out from the papers.

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Did you know that Python is
the 2nd most popular programming language
based on number of references?