Build it Yourself — Chatbot API with Keras/TensorFlow ModelStep-by-step solution with source code to build a simple chatbot on top of Keras/TensorFlow…
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Sentiment Analysis using Deep Learning techniques with India Elections 2019 — A Case study
The prominent parties standing for the elections, party leaders and representatives have a busy schedule organizing campaigns and convincing people…
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Visualizing ELMo Contextual VectorsContextual vectors can be useful for word sense disambiguation. Henry ChangBlockedUnblockFollowFollowingApr 15Issue with Word EmbeddingThere are difficulties…
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 ReadingThe Data Science Behind Natural Language Processing
What is natural language processing and how does it work?Natural language processing (NLP) is a discipline in computer science and…
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How Transformers WorkThe Neural Network used by Open AI and DeepMindGiuliano GiacagliaBlockedUnblockFollowFollowingMar 10Transformers are a type of neural network architecture that…
Continue ReadingA Step-by-Step Must-Read NLP Guide to Learn ELMo for Extracting Features from Text
Take a moment to ponder the difference between these two. The verb “read” in the first sentence is in the…
Continue ReadingWord Distance between Word Embeddings with Weight
Therefore, Huang et al. proposed an improvement and named Supervised Word Mover’s Distance (S-WMD). Introduce to Supervised Word Mover’s Distance (S-WMD)Before…
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 ReadingUnifying Word Embeddings and Matrix Factorization — Part 1
Unifying Word Embeddings and Matrix Factorization — Part 1The problems of viewing Word2vec as a neural network, and reviewing Levy & Goldberg’s attempted…
Continue ReadingLanguage Translation with RNNs
Language Translation with RNNsBuild a recurrent neural network (RNN) to translate English to FrenchThomas TraceyBlockedUnblockFollowFollowingFeb 22Image credit: xiandong79. github. ioThis post explores…
Continue ReadingSentiment Analysis with Deep Learning of Netflix Reviews
This is where we use the word-to-index map. Consider you want to get the embedding vector for the word “although”,…
Continue ReadingWord2vec from Scratch with NumPy
Word2vec from Scratch with NumPyHow to implement a Word2vec model with Python and NumPyIvan ChenBlockedUnblockFollowFollowingFeb 17IntroductionRecently, I have been working with several…
Continue ReadingIntroduction to Flair for NLP: A Simple yet Powerful State-of-the-Art NLP Library
# for i in range(10): print(corpus[i]) print(POS[i]) ### Removing blanks form sentence and pos ### corpus = [x for x…
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 ReadingCommunity Forums Meets Data Science
Can we help with your next project?” In addition, these members could be invited to higher level discussions (e. g.…
Continue ReadingContextual Embeddings for NLP Sequence Labeling
Contextual Embeddings for NLP Sequence LabelingContextual String Embeddings for Sequence LabelingEdward MaBlockedUnblockFollowFollowingFeb 2Text representation (aka text embeddings) is a breakthrough of solving…
Continue ReadingUsing Transfer Learning and Pre-trained Language Models to Classify Spam
Using Transfer Learning and Pre-trained Language Models to Classify SpamSteve MutuviBlockedUnblockFollowFollowingJan 31Transfer learning, an approach where a model developed for a…
Continue ReadingCreation of Sentence Embeddings Based on Topical Word Representations
Creation of Sentence Embeddings Based on Topical Word RepresentationsAn approach towards universal language understandingPhillip WenigBlockedUnblockFollowFollowingJan 31I am researching on word…
Continue ReadingData Augmentation for Natural Language Processing
A naive approach would be to use a lexicon such as WordNet, which has a fixed definition assigned to each…
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 ReadingAre BERT Features InterBERTible?
Better go catch it!Let’s take a look at another example, this time using the word pie. We generate the 5 sentences:pie…
Continue ReadingMust-Read Tutorial to Learn Sequence Modeling (deeplearning.ai Course #5)
Solving this gives us a 300 dimensional vector with a value equal to the embeddings of queen. We can use…
Continue ReadingIdentify Top Topics using Word Cloud
before the command and it’ll work like it is in a command line. I am using it to get the…
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