Contrary to popular believe, English has more than five or ten vowel sounds. The actual number is disputed because of…
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Word Embedding Fairness Evaluation
By Pablo Badilla and Felipe Bravo-Marquez. Word embeddings are dense vector representations of words trained from document corpora. They have become a…
Continue ReadingChemical element frequency in writing
How do the frequencies of chemical element names in English text compare to the abundance of elements in Earth’s crust?…
Continue ReadingWhat is Tokenization in NLP? Here’s All You Need To Know
Highlights Tokenization is a key (and mandatory) aspect of working with text data We’ll discuss the various nuances of tokenization,…
Continue ReadingAn Essential Guide to Pretrained Word Embeddings for NLP Practitioners
Overview Understand the importance of pretrained word embeddings Learn about the two popular types of pretrained word embeddings – Word2Vec…
Continue ReadingLemma, Lemma, Red Pyjama: Or, doing words with AI
It depends. Capitalization by itself doesn’t usually change the meaning of a word, so a computer can usually be told…
Continue ReadingCéline Van den Rul
The 5 Packages You Should Know for Text Analysis with RA Complete Overview of the Most Useful…A Guide to Mining and Analysing…
Continue ReadingBERT is changing the NLP landscape
By Phillip Green, Informatics4AI. Last year, I was worried that conversational AI would never shed its dunce cap. Today I am…
Continue ReadingQuaternion reference in the Vulgate
To contemporary ears “quaternion” refers to a number system discovered in the 19h century, but there were a couple precedents.…
Continue Reading[NLP] Performance of Different Word Embeddings on Text Classification
Photo by Kate Stone Matheson on Unsplash[NLP] Performance of Different Word Embeddings on Text Classificationcompared among word2vec, TF-IDF weighted, GloVe and doc2vecTom…
Continue ReadingXLNet — a clever language modeling solution
permutations — 362,880. If we sample from this permutations, pick a permutation, say 612934578 and apply the following rule:-Pick every number from…
Continue ReadingExplain NLP models with LIME & SHAP
'. join(map(str, exp. as_list(label=8))))It is obvious that this document has the highest explanation for label sql. We also notice that…
Continue ReadingJuan De Dios Santos
“Where today?” — Planning my Singapore trip with clustersOutlining travel plans with R, k-medoids and…Analyzing tweets from the polemical Pokemon-related #BringBackNationalDex tag with…
Continue ReadingProcessing Text data in Natural Language Processing
` * } @ : ; ^ |= &= += -= = /= *=Morphological NormalizationThis type of normalization is needed when there…
Continue ReadingText Processing Is Coming
Text Processing Is ComingHow to use Regular Expression (Regex) and the Natural Language Toolkit (NLTK) on Game of Thrones Book 1Madeline McCombeBlockedUnblockFollowFollowingJun…
Continue ReadingText Summarization using TF-IDF
Those Who Are ': {'resili': 0. 03225806451612903, 'stay': 0. 03225806451612903, 'game': 0. 03225806451612903, 'longer': 0. 03225806451612903, '“': 0. 03225806451612903, 'mountain':…
Continue ReadingDifferent techniques to represent words as vectors (Word Embeddings)
Different techniques to represent words as vectors (Word Embeddings)From Count Vectorizer to Word2VecKaran BhanotBlockedUnblockFollowFollowingJun 7Photo by Romain Vignes on UnsplashCurrently, I’m working…
Continue ReadingWord Embedding (Part II)
Word Embedding (Part II)Intuition and (some) maths to understand end-to-end GloVe modelMatyas AmroucheBlockedUnblockFollowFollowingApr 25The power of GloVeThe original issue of NLP (Natural Language…
Continue ReadingLiminal and subliminal
It occurred to me for the first time this morning that the words liminal and subliminal must be related, just…
Continue ReadingNoise Contrastive Estimation
Noise Contrastive EstimationA Gentle IntroductionZak JostBlockedUnblockFollowFollowingMay 21This article originally appeared on blog. zakjost. comIntroductionI have recently worked to understand Noise…
Continue ReadingHow subword helps on your NLP model?
How subword helps on your NLP model?Introduction to subwordEdward MaBlockedUnblockFollowFollowingMay 18Classic word representation cannot handle unseen word or rare word well. Character…
Continue ReadingChallenges in sentiment analysis: a case for word clouds (for now)
For example, if I only take the list of positive tweets and I get an aggregate sentiment score for the…
Continue ReadingRemembering the Tragedy of Sewol through Word Cloud Data Visualization
I extracted the keywords from my datasets using the online tool Tagxedo(http://www. tagxedo. com/), which I highly recommend other data…
Continue ReadingInvestigating the Machine Reading Comprehension Problem with Deep Learning
For machines it’s even harder; since language is highly flexible a sequence of words that you are looking for might…
Continue ReadingA Game of Words
With all the hype surrounding the show at the moment I thought it the perfect time to investigate how Data…
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