eugeneyan / applied-ml Goto Github PK
View Code? Open in Web Editor NEW๐ Papers & tech blogs by companies sharing their work on data science & machine learning in production.
License: MIT License
๐ Papers & tech blogs by companies sharing their work on data science & machine learning in production.
License: MIT License
I have a code that could use some machine learning. If you know anything about DNA
There's no doubt this is one of the best resources on applied ML. Market basket analysis is one of the key things in business. But using association rules on the datasets fails due to huge frequent itemset generations. Are there any resource here or your suggestions on it?
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Hi (:
First of all, thank you so much for gathering all this intel.
Just opening a very simple issue: on the Data Discovery section of the README file, there are two identical resources, cf. items 10 & 18 on the rendered blob. The only difference is that one of them also includes a link to the corresponding repo.
This is treasure! Thanks for collecting and sharing them across. I'm new to the world recommendation algorithms and have a basic understanding of common systems out there. These are certainly cutting edge. However, I find it hard to start or understand from these papers. Are there any video links explaining these or conference talks for the same?
It would be great if we can add a privacy-preserving machine learning section as well.
Collection
Please add NLP pipeline book.
Do you think having the year of publishing can be a good idea to have along with the names of the articles/papers? It can help understand the recency of articles and also the trend the industry is taking.
It would take a lot of time given the number of articles ๐ , but I can take it up if you are interested.
This article seems relevant under Search section -
https://github.blog/2023-02-06-the-technology-behind-githubs-new-code-search/
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