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The section "Recommendation Systems" of the book "Mining of Massive Datasets" is going to be examined in order to deepen the knowledge about recommendation system techniques.
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Using:
Mahout - https://mahout.apache.org/users/recommender/userbased-5-minutes.html
Spark MLlib - https://spark.apache.org/docs/latest/mllib-collaborative-filtering.html
LibRec - http://www.librec…
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Test recommendation mechanism for statistical significance.
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When using large number of classes (e.g. > 10000, e.g for recommender systems), `StratifiedShuffleSplit` is very slow when compared to `ShuffleSplit`. Looking at the code, I believe that the following…
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Hi!,
I'm really interested on contribute in my spare time on this project, it would be great for me port the Python libraries to Go, or help with this task, the problem is that after read the "Contri…
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I'm trying to use mlens in a system I'm developing but, based on the documentation and the code, it's not really clear to me what `propagate_features` values I should use given my data. Could you offe…
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I.e. something like `generate_from_array(array)`, where `array` is supposed to be an array-like with labels: `('a', 'b', 'c', 'a')` / `['a', 'b', 'c', 'a']` / `np.array([1, 2, 3, 2])`.
The counting i…
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Hi there,
working on deep learning for recommender systems I came across the Google Wide and Deep model (see [1] and [2]).
## Problem
In my application context there are users and items as well…
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In this issue, recommender system libraries (jcolibri, crab and possible other solutions) are examined in order to find out which one is the most suitable for this project.
Besides, concepts of case …