Overview Learn about the word and sentence embeddings Know the top 4 Sentence Embedding Techniques used in the Industry …
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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 ReadingDhruvil Karani
How does Python work?A simple explanation of how Python code is executed differently than older programming languages. Introduction to Principal Component…
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 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 ReadingHow to Develop a Face Recognition System Using FaceNet in Keras
Face recognition is a computer vision task of identifying and verifying a person based on a photograph of their face.…
Continue ReadingVisualizing Bias in Data using Embedding Projector
Visualizing Bias in Data using Embedding ProjectorUsing Open-Sourced Embedding Projector tool for Interactive Visualization and Interpretation of EmbeddingsParul PandeyBlockedUnblockFollowFollowingJun 6t-SNE…
Continue ReadingHow to Perform Face Recognition With VGGFace2 in Keras
Face recognition is a computer vision task of identifying and verifying a person based on a photograph of their face.…
Continue ReadingTiny 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 ReadingIntroducing PyTorch BigGraph
Introducing PyTorch BigGraphFacebook’s New Framework for Processing Large GraphsJesus RodriguezBlockedUnblockFollowFollowingApr 3Graphs are one of the fundamental data structures in machine learning applications.…
Continue ReadingFinding similar images using Deep learning and Locality Sensitive Hashing
Finding similar images using Deep learning and Locality Sensitive HashingA simple walkthrough on finding similar images through image embedding by…
Continue ReadingComparing complex NLP models for complex languages on a set of real tasks
Let’s assume that pre-training takes 400 days on one 1080Ti and let’s work from there:Starting from pre-trained vectors / n-grams — maybe…
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 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 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 ReadingA Neural Implementation of NBSVM in Keras
A Neural Implementation of NBSVM in KerasArun MaiyaBlockedUnblockFollowFollowingJan 30NBSVM is an approach to text classification proposed by Wang and Manning¹ that…
Continue ReadingSentiment Classification with Natural Language Processing on LSTM
")feature_result_tgt = nfeature_accuracy_checker(vectorizer=tfidf,ngram_range=(1, 3))Before we are done here, we should check the classification report. from sklearn. metrics import classification_reportcv =…
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