invoice2data
gensim
| invoice2data | gensim | |
|---|---|---|
| 2 | 18 | |
| 1,699 | 15,256 | |
| 1.6% | 0.9% | |
| 6.7 | 7.5 | |
| 8 days ago | 10 days ago | |
| Python | Python | |
| MIT License | GNU Lesser General Public License v3.0 only |
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invoice2data
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Utilize OpenAI API to extract information from PDF files
Using regex: to match patterns in text after converting the PDF to plain text. Examples include invoice2data and traprange-invoice. However, this method requires knowledge of the format of the data fields.
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Base64.ai – Extract text, data, photos and more from all types of docs
It's not really working. Tried 2 English PDF invoices. Normal format. One came back empty, the other only had the amount right.
I'm assuming they only trained on some specific documents (passport of country X, etc) and all others don't work.
If someone processes the same document all the time, then my invoice2data project may work better and is open source. It's based on Regx, rather than machine learning: https://github.com/invoice-x/invoice2data
gensim
- Aggregating news from different sources
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Understanding How Dynamic node2vec Works on Streaming Data
This is our optimization problem. Now, we hope that you have an idea of what our goal is. Luckily for us, this is already implemented in a Python module called gensim. Yes, these guys are brilliant in natural language processing and we will make use of it. 🤝
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Topic modeling --- allow multiple topics per statement
Try LDA as implemented in gemsin https://github.com/RaRe-Technologies/gensim
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Is it home bias or is data wrangling for machine learning in python much less intuitive and much more burdensome than in R?
Standout python NLP libraries include Spacy and Gensim, as well as pre-trained model availability in Hugginface. These libraries have widespread use in and support from industry and it shows. Spacy has best-in-class methods for pre-processing text for further applications. Gensim helps you manage your corpus of documents, and contains a lot of different tools for solving a common industry task, topic modeling.
- sentence transformer vector dimensionality reduction to 1
- Where to start for recommendation systems
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GET STARTED WITH TOPIC MODELLING USING GENSIM IN NLP
Here we have to install the gensim library in a jupyter notebook to be able to use it in our project, consider the code below;
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Show HN: I built a site that summarizes articles and PDFs using NLP
Nice work! I wonder if you're going the same challenges that gensim had for being generic in summarization.
For context:
> Despite its general-sounding name, the module will not satisfy the majority of use cases in production and is likely to waste people's time.
https://github.com/RaRe-Technologies/gensim/wiki/Migrating-f...
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[Research] Text summarization using Python, that can run on Android devices?
TextRank will work without any problems. https://radimrehurek.com/gensim/
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Topic modelling with Gensim and SpaCy on startup news
For the topic modelling itself, I am going to use Gensim library by Radim Rehurek, which is very developer friendly and easy to use.
What are some alternatives?
OCRmyPDF - OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched
BERTopic - Leveraging BERT and c-TF-IDF to create easily interpretable topics.
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
scikit-learn - scikit-learn: machine learning in Python
DeepSpeech - DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
MLflow - Open source platform for the machine learning lifecycle
silero-models - Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple
tensorflow - An Open Source Machine Learning Framework for Everyone
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Keras - Deep Learning for humans
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
flair - A very simple framework for state-of-the-art Natural Language Processing (NLP)