Fatemeh Rahimi
  • Member for 3 years, 1 month
  • Last seen more than a month ago
How to get sentence embedding using BERT?
20 votes

There is actually an academic paper for doing so. It is called S-BERT or Sentence-BERT. They also have a github repo which is easy to work with.

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BERT word embedings for finding word definition
4 votes

BERT generates contextualized word embeddings, which means that BERTprovides the most accurate embeddings when a word is in a sentence(context). For each of the words within the sentence, BERT will ...

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NLP data cleaning and word tokenizing
Accepted answer
3 votes

I summarize your questions and then try to answer under each bullet point: How to remove punctuation marks (e.g. # for hashtags which is used in social media) The first goto is a regular expression ...

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Preprocessing for Text Classification in Transformer Models (BERT variants)
3 votes

A quick experiment you can do is to once do the preprocessing steps that you usually do and then feed it to the model and get the results. And once feed the dataset as it is to the model to compare ...

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Masked Language Modeling on Domain-specific Data
1 votes

First I suggest reading the transformers paper. Couple of quick notes is that this model consists of an encoder and a decoder, and the original task the paper is trained on is machine translation. ...

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Tools for a data science job
1 votes

I think your question is not clear enough. You need to be exact about the job description. But I have a suggestion for you to figure this out on your own. Simply go to LinkedIn, look for the jobs you ...

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Using BM25 to rank words
1 votes

BM25 is usually used in information retrieval. In this task, you have a query and a lot of documents(maybe millions), and then you want to find a subset of these documents that are most relevant to ...

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Are there any good NLP APIs for comparing strings in terms of semantic similarity?
1 votes

I can give you some hint of doing so with deep learning approaches. It's easy to use gensim and sklearn python libraries. First, you need to extract the word embeddings which are vector of numbers to ...

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Using a JSON dataset for lstm
Accepted answer
1 votes

I'm not sure how you are processing your JSON file right now. But Pandas is really convinient way for doing so. So for start you can read the file with pandas, following instructions here. A ...

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How do I split contents in a text that would include two or more different themes (context) in NLP?
0 votes

First reading the question I thought this is very easy and I started searching and trying out some libraries (i.e. nltk, and spacy). Here are my attempts and clearly showing that none of them works. I ...

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where to store embeddings for similarity search?
0 votes

My answer would be it depends on your creativity. I've seen people storying them in numpy files, pickle files, graph databases and etc. So I would say it doesn't matter where you store them, It's your ...

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