Natural Language Processing

A Practitioner's Guide to Natural Language Processing (Part I) — Processing & Understanding Text

However, based on all the excellent feedback I’ve received from all my readers (yes all you amazing people out there!), the main objective and …

Natural Language Processing

Auto-generated materials database of Curie and Néel temperatures via semi-supervised relationship extraction

Data Descriptor |<p>Open | Published: 19 June 2018<p>Callum J. Court<br>• & Jacqueline M. Cole<p><i>Scientific Data</i> <b>volume 5</b>, Article number: 180111 (2018) | Download …

Google Scholar

Pivoted document length normalisation | RARE Technologies

<b>Term frequency</b>: For a word (or term) t, the term frequency is denoted by tft,d and the frequency of each term in a document d is denoted by ft,d then …

Data Science

Sent2Vec: An unsupervised approach towards learning sentence embeddings | RARE Technologies

<i>Comparison of sentence embedding techniques by Prerna Kashyap, a RARE Incubator student. Prerna implemented a new document embedding model in Gensim,</i> …

Machine Learning

KS3 Computer Science - Introduction to computational thinking - Revision 1

What is computational thinking?<p>Computers can be used to help us solve problems. However, before a problem can be tackled, the problem itself and the ways in which it could be solved need to be understood.<p>Computational thinking allows us to do this.<p>Computational thinking allows us to take a complex …

Computer Science

NLP In Under 5 Min

AI is the sexiest trend in tech, and NLP (Natural Language Processing) is one of its many branches. NLP is the ability of a machine to understand and …

Data Science

Text Classification: The First Step Toward NLP Mastery

Build a Strong Baseline by Following Simple Steps<p><b>Natural Language Processing</b> (<b>NLP</b>) is a wide area of research where the worlds of artificial …

Machine Learning

In Search of Coherence and Consensus: Measuring the Interpretability of Statistical Topics

<b>Fred Morstatter, Huan Liu</b>; 18(169):1−32, 2018.<p>Abstract<p>Topic modeling is an important tool in natural language processing. Topic models provide two …

Machine Learning

How are ‘immigrant workers’ represented in Korean news reporting?—A text mining approach to critical discourse analysis | Digital Scholarship in the Humanities

The present study explores the usefulness of a text mining approach to investigating the representation of minorities in news reporting. The question …

Humanities

natural language to sql (from examples), learning sql from examples

Disclaimer: May be has been asked before, but couldn't find something that could fit the bill. The closest I got to was Automatic SQL query …

Sql

11 texts you only get from your dad

3) The 'I hate texting' text.<p>1. The 'buying mum a present' text<p>2. The 'rolling news service' text<p>3. The 'I hate texting' text<p>4. The 'trying to be your fellow fan' text<p>5. The 'practical advice' text<p>6. The 'learning text abbreviations and sounding like a teenager' text<p>7. The 'bored at home' text<p>8. …

Text Messaging

Understanding the Working of Universal Language Model Fine Tuning (ULMFiT)

<b>Transfer Learning</b> in <b>natural language processing</b> is an area that had not been explored with great success. But, last month (May 2018), <b>Jeremy Howard</b> …

Deep Learning

Speech Synthesis as a Service

MLaaS Part 2: Speaker on the wall, who’s got the best voice of them all?<p>Natural-sounding robotic voices<p>With the increasing performance of …

Text-To-Speech

Clinical natural language processing for predicting hospital readmission

Doctors have always written clinical notes about their patients — originally, the notes were on paper and were locked away in a cabinet. Fortunately …

Data Science

PubMed Phrases, an open set of coherent phrases for searching biomedical literature

Altmetric: 3<p>More detail<p>Data Descriptor |<p>Open | Published: 12 June 2018<p>Sun Kim<br>• , Lana Yeganova<br>• , Donald C. Comeau<br>• , W. John Wilbur<br>• & Zhiyong Lu<p><i>Scientific</i> …

Google Scholar

Health Language Analytics takes out top prize at NSW iAwards

Sydney's Health Language Analytics (HLA) took out the Premier’s award for public sector innovation at the NSW iAwards last week for its Horizon …

Analytics

59 - Weakly Supervised Semantic Parsing With Abstract Examples, with Omer Goldman

Parsing

Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis. (arXiv:1806.04558v1 [cs.CL])

Authors: Ye Jia, Yu Zhang, Ron J. Weiss, Quan Wang, Jonathan Shen, Fei Ren, Zhifeng Chen, Patrick Nguyen, Ruoming Pang, Ignacio Lopez Moreno, Yonghui …

Text-To-Speech

Semantic Web Company: The Web As We Know It Has Reached Its Limits Due To A Lack Of Semantics

SSupported by SproutSocial.com – helps organisations collaborate and publish across multiple social profiles and networks;<p>Below is our recent …

Artificial Intelligence

PyTorch Sentiment Analysis

This repo contains tutorials covering how to do sentiment analysis using PyTorch 0.4 and TorchText 0.2.3 using Python 3.6.<p>The first 2 tutorials will …

Tutorials

Conversational AI tutorial, RNNs for particle physics, InfoGAN, NLP Coursera, NLP book, killer robots, Code2pix, Google AI principles, relational reasoning

http://newsletter.ruder.io/issues/conversational-ai-tutorial-rnns-for-particle-physics-infogan-nlp-coursera-nlp-book-killer-robots-code2pix-google-ai- …

Particle Physics

compare table last two rows value and highlighted update field

check table rows last recently two update filled and compare updated value and highlighted that change//its all depends django historical records

Natural Language Processing

Finding Syntax in Human Encephalography with Beam Search. (arXiv:1806.04127v1 [cs.CL])

Recurrent neural network grammars (RNNGs) are generative models of (tree,string) pairs that rely on neural networks to evaluate derivational choices. …

Computer Science

Keras + Universal Sentence Encoder = Transfer Learning for text data

We are going to build a Keras model that leverages the pre-trained “Universal Sentence Encoder” to classify a given question text to one of the six …

Deep Learning

Embedding Machine Learning Models to Web Apps (Part-1)

Source (Pixabay)The best way to learn data science is by doing it, and there’s no other alternative . From this post, I am going to reflect my …

Machine Learning

Probabilistic FastText for Multi-Sense Word Embeddings. (arXiv:1806.02901v1 [cs.CL])

Authors: Ben Athiwaratkun, Andrew Gordon Wilson, Anima AnandkumarWe introduce Probabilistic FastText, a new model for word embeddings that can …

arXiv

Best Papers

The ACL 2018 organising committee is please to announce the following best papers:<p><b>Best Long Papers</b><p><i>Finding syntax in human encephalography with beam</i> …

Artificial Intelligence

Proving commutativity of type level addition of natural numbers

I'm playing around with what tools haskell offers for dependently typed programming. I have promoted a GADT representing natural numbers to the kind …

Programming

Can a bot learn a second language?

Creating a chatbot that can understand and use a language other than English can be an ambitious task. Chatbots are still in their early days and …

Chatbots

Coding & English Lit: Natural Language Processing in Python

<i>This beginner-level tutorial shows you how to use Python and the Natural Language Toolkit (NLTK) to analyze texts imported from URLs and downloaded</i> …

Python Programming