langhuan

Light weight labeling engine (by raynardj)
Review NLP Ner Labeling labeling-tool Classification tagging-tool named-entity-recognition Data Science Machine Learning
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Monitoring that respects your time & budget
APM, error tracking, and dashboards for modern web apps. Ten-minute setup, transparent flat pricing, and support from engineers who actually use the product.
www.appsignal.com
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raynardj
langhuan

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    A sentiment analysis model trained with Kaggle GPU on 1.6M examples, used to make inferences on 220k tweets about Messi and draw insights from their results.

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  3. embedders

    1 langhuan VS embedders

    With embedders, you can easily convert your texts into sentence- or token-level embeddings within a few lines of code. Use cases for this include similarity search between texts, information extraction such as named entity recognition, or basic text classification.

  4. Universal Data Tool

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    Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.

  5. markup

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  6. NL_Parser_using_Spacy

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  8. refinery

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  10. nlphose

    4 langhuan VS nlphose

    Enables creation of complex NLP pipelines in seconds, for processing static files or streaming text, using a set of simple command line tools. Perform multiple operation on text like NER, Sentiment Analysis, Chunking, Language Identification, Q&A, 0-shot Classification and more by executing a single command in the terminal. Can be used as a low code or no code Natural Language Processing solution. Also works with Kubernetes and PySpark !

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2
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1.8
almost 5 years ago

The primary programming language of langhuan is Jupyter Notebook.

Popular Comparisons

  1. langhuan VS Twitter-sentiment-analysis
  2. langhuan VS embedders
  3. langhuan VS Universal Data Tool
  4. langhuan VS markup
  5. langhuan VS NL_Parser_using_Spacy
  6. langhuan VS nlpaug
  7. langhuan VS refinery
  8. langhuan VS nlphose

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Monitoring that respects your time & budget
APM, error tracking, and dashboards for modern web apps. Ten-minute setup, transparent flat pricing, and support from engineers who actually use the product.
www.appsignal.com
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