pyDenStream
dedupe
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| pyDenStream | dedupe | |
|---|---|---|
| 1 | 9 | |
| 9 | 3,970 | |
| - | 0.9% | |
| 5.2 | 7.1 | |
| about 2 months ago | about 1 month ago | |
| Python | Python | |
| - | MIT License |
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.
pyDenStream
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[P] Implementation of DenStream
The implementation can be found here: https://github.com/MrParosk/pyDenStream
dedupe
- Using deep learning for Fuzzy Matching
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String distance based network for fuzzy matching?
I think this problem is known as data deduplication, in particular, entity deduplication. I googled a bit and it seems approaches vary from manual deduplication to some sort of active learning (if I am not mistaken). I am also curios if pre-trained transformer-based cross encoders can provide any good results (they are trained on sentences I think, but may be worth a try). Another problem here is how to measure progress (compare different approaches)?
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What's the toughest DE problem you faced in your work career?
I've had a good experience in the past with the dedupe package for these type activities. Unsure if it works for out-of-core type situations though, as my data set fit easily into memory.
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Model detects duplicate records
Data deduplication is a super common problem, so it's useful experience to work on it. It's generally useful for companies, but I don't think it could be sold as a product unless is solving a very complicated, domain-specific de-duping problem. Otherwise, there are generic, open source de-duping tools such as: dedupe. It sounds like your model is similar to that.
- [D] Suggestions for large-scale company name standardization?
- Entity Resolution with Magniv
- How to do fuzzy matching in Redshift? A Python UDF, for example?
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[OC] Media bias? US Sunday news shows book Republicans more than Democrats: Three of the five top Sunday news shows, altogether watched by almost 8 million people weekly, featured Republican partisans more often than Democrats in episodes aired this year through Oct. 31.
Tools used: Python to scrape guest lists, dedupeio to better identify guests, Google Sheets to store and analyze the data, and Datawrapper to make the charts.
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Does there exist a python package that clears the dataset/columns in terms of exact and similar duplicates?
Try https://github.com/dedupeio/dedupe
What are some alternatives?
stringlifier - Stringlifier is on Opensource ML Library for detecting random strings in raw text. It can be used in sanitising logs, detecting accidentally exposed credentials and as a pre-processing step in unsupervised ML-based analysis of application text data.
splink - Fast, accurate and scalable probabilistic data linkage with support for multiple SQL backends
uis-rnn - This is the library for the Unbounded Interleaved-State Recurrent Neural Network (UIS-RNN) algorithm, corresponding to the paper Fully Supervised Speaker Diarization.
imgdupes - Identifying and removing near-duplicate images using perceptual hashing.
impfuzzy - Fuzzy Hash calculated from import API of PE files
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
bees - Best-Effort Extent-Same, a btrfs dedupe agent
hazelcast-python-client - Hazelcast Python Client
relevanceai - Home of the AI workforce - Multi-agent system, AI agents & tools
notes - notes on the tools in my Unix/Linux toolbox, dotfiles, etc