A bitesize explanationPaul MayBlockedUnblockFollowFollowingApr 23NLP keeps being bounded about as a magic panacea or a digital tower of babel and…
Continue Readingwords
Tiny Dataset Hypothesis Testing by Projecting Pretrained-Embedding-Space Onto KDE-Mixed Space
Tiny Dataset Hypothesis Testing by Projecting Pretrained-Embedding-Space Onto KDE-Mixed SpaceA method mainly for aiding in quick prototyping, guided topic modeling,…
Continue ReadingMulticlass Text Classification From Start To Finish
Multiclass Text Classification From Start To FinishRob SalgadoBlockedUnblockFollowFollowingMar 31So you have some text and you want to classify it. So you…
Continue ReadingWord Vectors and Lexical Semantics (Part 1)
Word Vectors and Lexical Semantics (Part 1)Hafidz ZulkifliBlockedUnblockFollowFollowingMar 27The following are my personal notes based on the Deep NLP course by…
Continue ReadingQuestion pairs identification
Obviously!Improved Customer Experience — Faster responses to questions. Re-use content — If a question has been answered before, it is very efficient to use…
Continue ReadingQuestions pairs identification
Obviously!Improved Customer Experience — Faster responses to questions. Re-use content — If a question has been answered before, it is very efficient to use…
Continue ReadingHaving fun with NLP and Game of Thrones dialogues.
This article will try to answer those questions. Before anything I would like to mention these two guys whose work…
Continue ReadingUsing word2vec to Analyze News Headlines and Predict Article Success
word2vec can help us answer these questions, and more. Charlene ChamblissBlockedUnblockFollowFollowingMar 3Word embeddings are a powerful way to represent the latent…
Continue ReadingEssential NLP Tools, Code, and Tips
Essential NLP Tools, Code, and Tips#ODSC – Open Data ScienceBlockedUnblockFollowFollowingMar 1In a previous article, we introduced the influential impact of natural…
Continue ReadingWhat the heck is Word Embedding
What the heck is Word EmbeddingLooking at text data through the lens of Neural NetsSamarth AgrawalBlockedUnblockFollowFollowingFeb 10Photo by Dmitry Ratushny on UnsplashWord…
Continue ReadingUsing NLP to build a search & discovery app for Regulators
Using NLP to build a search & discovery app for RegulatorsAbizer JafferjeeBlockedUnblockFollowFollowingFeb 7Regulations need to be updated constantly in this…
Continue ReadingA snapshot of change in popular music in the last decade: 2008 vs 2018
We explore chart-toppers of 2008 and 2018 with some visualizations. Bored AnalyticsBlockedUnblockFollowFollowingFeb 4The method:We figured a good starting point would…
Continue ReadingPreliminary thoughts on Voynichese Part of Speech tagging
Preliminary thoughts on Voynichese Part of Speech taggingMarco PonziBlockedUnblockFollowFollowingFeb 1Software tools for unsupervised Part of Speech (POS) tagging have been around…
Continue ReadingLearning NLP Language Models with Real Data
There are far to many possible sentences in this method that would need to be calculated and we would like…
Continue ReadingHow I built a Cannabis Recommendation app using Topic Models and Latent Dirchlet Allocation (LDA) ~Non-Technical ~
For instance, if we had a document with three words in it, “dog eats food”, each word would be converted…
Continue ReadingYour Guide to Natural Language Processing (NLP)
(meaning that you can be diagnosed with the disease even though you don’t have it). This recalls the case of…
Continue ReadingHow Smart is Your News Source?
How Smart is Your News Source?Text Data Analysis of 21 Different News OutletsMichael TaubergBlockedUnblockFollowFollowingJan 12I think it’s more important than ever to…
Continue ReadingCoding & Foreign Language Lit: Analyzing Dante’s Inferno with Python NLTK
First order of business, we’ll need to create a stemmer. You can create an Italian stemmer like so:stemmer = SnowballStemmer("italian")If…
Continue ReadingNLP Text Visualization & Twitter Sentiment Analysis in R
NLP Text Visualization & Twitter Sentiment Analysis in RRituparna GuptaBlockedUnblockFollowFollowingJan 8The FIFA World Cup, often simply called the World Cup, is…
Continue ReadingNeural Networks and Philosophy of Language
Neural Networks and Philosophy of LanguageWhy Wittgenstein’s theories are the basis of all modern NLPMassimo BelloniBlockedUnblockFollowFollowingJan 7Word embeddings is probably one of…
Continue ReadingThe General Ideas of Word Embeddings
The building stones are therefore characters instead of words.The word embeddings outputted by FastText look very similar to the ones…
Continue ReadingMail Processing with Deep Learning: A Case Study
Typed LettersHubert’s team decided early on it would be best for their deep learning space to deal with handwritten and typed…
Continue ReadingNet upvote prediction and subreddit-based sentence completion for Reddit comments:
The computational complexity of training this seq2seq model is higher than training the word embedding neural language model, so in…
Continue ReadingAn introduction to Bag of Words and how to code it in Python for NLP
It creates a vocabulary of all the unique words occurring in all the documents in the training set.In simple terms,…
Continue ReadingI wrote a Python program to calculate the most commonly used words in subreddits. Here’s what I found…
I used a set instead of a regular list for more efficient lookup time O(1) vs O(n)Yikes, I’m still adding…
Continue Reading