Why NLP is a Great First AI Solution for Businesses
The world of the C-suite isn’t quite ready to embrace artificial intelligence just yet. That’s according to an oft-cited Accenture study from late 2016, which found that less than half of the 1,700 business leaders interviewed in a global sample would feel comfortable trusting the advice of AI “in... Read more
The Mystical Underpinnings of Facebook’s Anti-Fake News Algorithms
Imagine you’re Rene Descartes, data scientist at Facebook in charge of saying true things. Problem is, your only input is what people say, and everybody lies. It’s not a moral failure, it’s just that you’ve built Facebook into the world’s largest integrated content distribution machine, and convincing people of things... Read more
Text Classification with TensorFlow Estimators
Note: This post was written together with the awesome Julian Eisenschlos and was originally published on the TensorFlow blog. Hello there! Throughout this post we will show you how to classify text using Estimators in TensorFlow. Here’s the outline of what we’ll cover: Loading data using Datasets. Building baselines using pre-canned estimators.... Read more
Machine Learning Helps Humans Perform Text Analysis
The rise of Big Data created the need for data applications to be able to consume data residing in disparate databases, of wildly differing schema. The traditional approach to performing analytics on this sort of data has been to warehouse it; to move all the data into one place... Read more
What lies beyond Big Data Analysis?
Beyond big data analysis lies an innovation known as cognitive analysis, which is capable of providing insights with minimum human support. Information accumulating from disparate sources, differing in formats, is known as big data. This data is essential for organizations as it is capable of providing intuitive insights that... Read more
Text Analysis in Excel: Real world use-cases
Last month, we launched an Excel add-in, a solution for using ParallelDots NLP APIs to do text analysis on unstructured data without writing a single line of code. The Excel add-in is very easy to use and provides a convenient, yet effective solution for your text analysis needs. In an... Read more
Making a machine learning model usually takes a lot of crying, pain, feature engineering, suffering, training, debugging, validation, desperation, testing and a little bit of agony due to the infinite pain. After all that, we deploy the model and use it to make predictions for future data. We can run our little devil on a batch... Read more
Deep Learning Research Review Week 3: Natural Language Processing
This is the 3rd installment of a new series called Deep Learning Research Review. Every couple weeks or so, I’ll be summarizing and explaining research papers in specific subfields of deep learning. This week focuses on applying deep learning to Natural Language Processing. The last post was Reinforcement Learning and the post before was... Read more
You weren’t supposed to actually implement it, Google
Last month, I wrote a blog post warning about how, if you follow popular trends in NLP, you can easily accidentally make a classifier that is pretty racist. To demonstrate this, I included the very simple code, as a “cautionary tutorial.” The post got a fair amount of reaction. Much... Read more
A decade of using text-mining for citation function classification
Academic work is typically filled with references to previous work. Unfortunately, most of these references have, at best, a tangential relevance. Thus you cannot trust that a paper that cites another actually “builds on it”. A more likely scenario is that the authors of the latest paper did not... Read more
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