wakaranai
An educational tool for learning hiragana and katakana (by guidanoli)
scattertext
Beautiful visualizations of how language differs among document types. (by JasonKessler)
wakaranai | scattertext | |
---|---|---|
1 | 3 | |
0 | 2,203 | |
- | - | |
7.0 | 4.7 | |
10 months ago | 2 months ago | |
Python | Python | |
GNU General Public License v3.0 only | Apache License 2.0 |
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.
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.
wakaranai
Posts with mentions or reviews of wakaranai.
We have used some of these posts to build our list of alternatives
and similar projects.
-
wakaranai (わからない) — test your hiragana and katakana skills
GitHub: https://github.com/guidanoli/wakaranai
scattertext
Posts with mentions or reviews of scattertext.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-04-27.
-
Clustering of text - Where to start?
If what you want is to determine how similar two categories are, or to learn something about the structure or words that compose those categories, you might consider word shift graphs or Scattertext.
- [Data] Principali parole degli ultimi (circa) 200 post sul sub
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Alternate approaches to TF-IDF?
Other suggestions: Take a look at Scattertext. Compare keywords to the problem of aspect extraction. I think an underutilized way to look at textual data when you have a single group of interest is the word-frequency-based odds ratio.