NLP/Text Analytics Archives - Page 2 of 8 - Open Data Science - Your News Source for AI, Machine Learning & more

NLP/Text Analytics

An Idiot’s Guide to Word2vec Natural Language Processing

NLP/Text Analytics Natural Language Processingposted by Spencer Norris, ODSC November 15, 2018

Word2vec is arguably the most famous face of the neural network natural language processing revolution. Word2vec provides direct access to vector representations of words, which can help achieve decent performance across a variety of tasks machines are historically bad at. For a quick examination of how word vectors work,... Read more

Tracking the Progress in Natural Language Processing

NLP/Text Analyticsposted by Sebastian Ruder November 9, 2018

This post introduces a resource to track the progress and state-of-the-art across many tasks in NLP. Go directly to the document tracking the progress in NLP. Research in machine learning and in natural language processing (NLP) is moving so fast these days, it is hard to keep up. This... Read more

Sentiment Analysis in R Made Simple

Modeling NLP/Text Analytics R Natural Language Processing R sentiment analysisposted by Daniel Gutierrez, ODSC October 24, 2018

Sentiment analysis is located at the heart of natural language processing, text mining/analytics, and computational linguistics. It refers to any measurement technique by which subjective information is extracted from textual documents. In other words, it extracts the polarity of the expressed sentiment in a range spanning from positive to... Read more

The Art of Building a Chatbot

Modeling NLP/Text Analyticsposted by Alexander Osipenko September 17, 2018

With the development of deep learning and NLP chatbots become more and more popular. The hype for chatbots is already high and it will be increasing for the next several years. “By 2020, over 50% of medium to large enterprises will have deployed product chatbots” — Van Baker, research vice president... Read more

NLP: Extracting the Main Topics from your Dataset Using LDA in Minutes

Modeling NLP/Text Analyticsposted by Priya Dwivedi September 5, 2018

I recently started learning about Latent Dirichlet Allocation (LDA) for topic modelling and was amazed at how powerful it can be and at the same time quick to run. Topic Modelling is the task of using unsupervised learning to extract the main topics (represented as a set of words)... Read more

NLP — Building a Question Answering model

Modeling NLP/Text Analytics NLPposted by Priya Dwivedi September 3, 2018

I recently completed a course on NLP through Deep Learning (CS224N) at Stanford and loved the experience. Learnt a whole bunch of new things. For my final project I worked on a question answering model built on Stanford Question Answering Dataset (SQuAD). In this blog, I want to cover the... Read more

Using Object Detection for a Smarter Retail Checkout Experience

Modeling NLP/Text Analytics Natural Language Processing|NLPposted by Priya Dwivedi August 27, 2018

I have been playing around with the Tensorflow Object Detection API and have been amazed by how powerful these models are. I want to share the performance of the API for some practical use cases. The first use case is a smarter retail checkout experience. This is a hot field right... Read more

A Research-Oriented Look at the Evolution of Word Embedding: Part II

Modeling NLP/Text Analytics language NLP word embeddingposted by Kaylen Sanders, ODSC August 17, 2018

This article is the second article in a two-part series about the evolution of word embedding as told through the context of five research papers. It picks up in midst of the 1990s. To view the first article, click here. A Shift Towards Automatic Feature Generation: Latent Dirichlet Allocation... Read more

A Research-Oriented Look at the Evolution of Word Embedding: Part I

Modeling NLP/Text Analyticsposted by Kaylen Sanders, ODSC August 6, 2018

Introduction “You shall know a word by the company it keeps,” insisted John R. Firth, a British linguist who performed pioneering work on collocational theories of semantics. What Firth meant by his 1957 quote was that interrogating the context in which a word is found offers clues to the... Read more

NLP’s ImageNet Moment Has Arrived

Modeling NLP/Text Analyticsposted by Sebastian Ruder July 24, 2018

This post originally appeared at TheGradient and was edited by Andrey Kurenkov, Eric Wang, and Aditya Ganesh. Big changes are underway in the world of Natural Language Processing (NLP). The long reign of word vectors as NLP’s core representation technique has seen an exciting new line of challengers emerge: ELMo, ULMFiT, and the OpenAI transformer. These works made headlines by... Read more