Two Minute Papers explores the paper “Learning to Generate Reviews and Discovering Sentiment” (demo) in this latest video.
Here’s an interesting article on a deep learning toolkit for NLP.
Why are the results of the latest models so difficult to reproduce? Why is the code that worked fine last year not compatible with the latest release of my deep learning framework? Why is a baseline benchmark meant to be straightforward so difficult to set up? In today’s world, […]
Siraj Raval has put together a course on Natural Language Processing. Get ready, it’s going to be one heck of a ride.
Two Minute Papers explores the paper “Direct speech-to-speech translation with a sequence-to-sequence model.” Check out the voice samples as well.
Here’s an interesting story about data analytics, specifically NLP, and data visualization can breathe new life into classic works of literature.
Phil Harvey, a Cloud Solution Architect at Microsoft in the UK, used the company’s Text Analytics API on 19 of The Bard’s plays. The API, which is available to anyone as part of Microsoft’s Azure Cognitive Services, can be used to identify sentiment and topics in text, as well as pick out key phrases and entities. This API is one of several Natural Language Processing (NLP) tools available on Azure.
As an added bonus, I think there should be an AMC series set in Elizabethan times mirroring the events of Breaking Bad.
Natural Language Processing (NLP) is the field of Artificial Intelligence dedicated to enabling computers to understand and communicate in human language.
NLP is only a few decades old, but we’ve made significant progress in that time.
In this video, Siraj Raval covers how its changed over the years, then how you can easily build an NLP app that can either classify or summarize text.
This is incredibly powerful technology that anyone can freely use.
OpenAI raised some eyebrows last month when it announced it had figured out a way to get an AI to write more naturally. They, however, decided not to release their entire research for fear that it could cause havoc.
Last month, researchers at OpenAI revealed they had built software that could perform a range of natural language tasks, from machine translation to text generation. Some of the technical details were published in a paper, though the majority of materials was withheld for fear that it could be used maliciously to create spam-spewing bots or churn out tons of fake news. Instead, OpenAI released a smaller and less effective version nicknamed GPT-2-117M.
The one and only Siraj Raval explores sentiment analysis as part of his Data Lit class.