flair
gensim
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flair | gensim | |
---|---|---|
9 | 18 | |
13,487 | 15,125 | |
0.9% | 1.0% | |
9.4 | 7.5 | |
7 days ago | 28 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | GNU Lesser General Public License v3.0 only |
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.
flair
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Artificial Intelligence sentiment analysis of the Harry Potter movies. The greener the edge the happier the conversations, the bigger the edge the more they talk. Made by me.
The code of the module is available there for easy access: https://github.com/flairNLP/flair
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The Spacy NER model for Spanish is terrible
Had the same experience with the german model in spacy (but tbh, the quailty of my textdata was bad). A bert based approach with flair really improved my results. I think there is a spanish pretrained model also available
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German POS Corpus for Commercial use
I had the same problem a couple years ago. I think Flair, form Zalando uses a different Corpus. However, it's not great and I am pretty sure they are infringing the license anyway...
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SpaCy VS Transformers for NER
For NER, if you don't need the full toolkit of spacy, I'd highly recommend checking out Flair. It will likely run faster than transformer-based models (like en_core_web_trf) and it tends to be one of the best performing approaches to NER.
gensim
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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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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.
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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.
- Unsupervised Learning for String Matching in Python - can I have advice on how to go about this?
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How to build a search engine with word embeddings
We will be using gensim to load our Google News pre-trained word vectors. Find the code for this here.
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The Levenshtein Distance in Production
> Problem statement: the Levenshtein distance is a string metric for measuring the difference between two sequences
Another variant is "I have a bunch of words (a dictionary) and one query word, and want to find all words from the dictionary that are close to the query word".
This leads to an interesting class of problems, because you can do clever things where you precompute search structures (Levenshtein automata [0]) from the dictionary. The similarity queries then run (much) faster – in production, performance matters.
We recently merged a PR like that into Gensim [1].
This gave a ~1,500x speed-up compared to naively comparing all pairwise strings with Levenshtein distance. A difference between the training step running for years (=unusable) and minutes.
[0] http://blog.notdot.net/2010/07/Damn-Cool-Algorithms-Levensht...
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Koan: A word2vec negative sampling implementation with correct CBOW update
Apparently it did: https://github.com/RaRe-Technologies/gensim/issues/1873
What are some alternatives?
BERTopic - Leveraging BERT and c-TF-IDF to create easily interpretable topics.
scikit-learn - scikit-learn: machine learning in Python
MLflow - Open source platform for the machine learning lifecycle
spacy-models - 💫 Models for the spaCy Natural Language Processing (NLP) library
tensorflow - An Open Source Machine Learning Framework for Everyone
BERT-NER - Pytorch-Named-Entity-Recognition-with-BERT
Keras - Deep Learning for humans
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
fuzzywuzzy - Fuzzy String Matching in Python
GuidedLDA - semi supervised guided topic model with custom guidedLDA
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow