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Understand how you can leverage Natural Language Processing (NLP) pre-trained models to summarize live twitter data based on hashtags.
BERT is a really powerful language representation model that has been a big milestone in the field of NLP. Lets explore it in this article.
In this article, you will create an AI that would generate text based on Elon Musk's previous Twitter postings.
A word cloud is a visual representation object for text processing. Here is a beginners guide to create a word cloud or tag cloud in python.
The Seq2Seq( sequence to sequence) model is a special class of RNNs used to solve complex language problems.
Sentence embedding techniques represent entire sentences and their semantic information, etc as vectors. Let us have a look at the top ones
Learn Information Retrieval, Vector Space Model and Mean Precision Average. Use word2vec on an Information Retrieval project based on a vector space model.
Texthero is a simple Python toolkit that provides quick and easy tools to let you preprocess, represent, map into vectors and visualize text data.
Understand NLG concepts such as dataset preparation, how a neural language model is trained, and finally Natural Language Generation process in PyTorch.
MobileBERT introduces bottlenecks in the transformer blocks, which allows us easily to distill the knowledge from larger teachers into smaller students.
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