Can you recommend open source AI libraries for text analysis?
Sergei Petrov
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William Gump@xyz_333
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Absolutely, Sergei! For text analysis, you should definitely check out NLTK for natural language processing tasks, and SpaCy for more advanced text analytics and language understanding.
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NLTK, spaCy, Gensim, Scikit learn, TensorFlow.
@priyankamandal thanks for sharing!
Textblob, Genism,SpaCy, Polyglot, Scikit-learn,NLTK
code-ray
@apoorva_goel3 do you have with some of these already a little experience?
@niklas_mengele I will not say I have much experience but sometimes I use them for my studies
TextBlob is a simple library for processing textual data. It provides a consistent API for diving into common natural language processing tasks.
@dennis_harris1 thanks
Hugging Face's transformers library offers pretrained state-of-the-art language models like BERT, GPT and RoBERTa. So, pretty much as good as it gets. You can use it in TensorFlow and PyTorch DL frameworks, usually depending on what you are working with; both should be quite good for text analysis tasks.
@sergeipetrov I've used BERT, DistilBERT and RoBERTa in Tensorflow for NLP tasks, and was quite happy with it. They're appropriate for your task as well. It's best to experiment with different models, and you can also try the GPT.
@sergeipetrov for sure
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Certainly! Some top open-source AI libraries for text analysis include NLTK, spaCy, Gensim, Scikit-learn, and TensorFlow/PyTorch. Each offers unique capabilities, so choose based on your project needs. Happy analyzing!
@qudsia_ali I'm trying different things to analize product insights better.
Certainly! Some popular open-source AI libraries for text analysis include NLTK (Natural Language Toolkit), spaCy, Gensim, and TextBlob. These libraries offer a wide range of functionalities such as tokenization, part-of-speech tagging, sentiment analysis, and more, making them valuable resources for text analysis tasks. Alverna used it.
@sehrish_rasool1 thank you!
Tensorflow