The term “NLP”—or natural language processing—encompasses a wide range of business use cases that are mostly text based. Consider that people use text to record and transmit their communications in general, and, as such, it’s one of the most widely available and “interoperable” data formats. While some industry sectors such as finance and healthcare haveContinue reading “NLP Survey Results: An Overview”
Tag Archives: nlp
2020 NLP Survey Report
By Ben Lorica and Paco Nathan. Learn how Natural Language Processing (NLP) technologies are being used today—the 2020 NLP Survey Report includes a detailed analysis of NLP technologies being implemented by businesses, budgets, trends, widely used tools and cloud platforms, and common use cases. The online survey ran for 41 days (July 5 to AugustContinue reading “2020 NLP Survey Report”
An intuitive overview of recent advances in automated reading comprehension, Part II
Recent progress in automated conversational question answering, with natural sounding answers in the context of the flow of conversation. By David Talby. [Part I: Recent progress in automated question answering about facts in Wikipedia articles.] Part one of this series showed recent progress in automated question answering about facts in Wikipedia articles. You may haveContinue reading “An intuitive overview of recent advances in automated reading comprehension, Part II”
An intuitive overview of recent advances in automated reading comprehension, Part I
Recent progress in automated question answering about facts in Wikipedia articles. By David Talby. NLP Summit: Join David Talby, Kira Radinsky, Amy Heineike, Clément Delangue, Joel Grus, Piero Molino, and many other speakers at the first NLP Summit, a FREE virtual conference which takes place in early October. One day – not next year,Continue reading “An intuitive overview of recent advances in automated reading comprehension, Part I”
Using machine learning to improve dialog flow in conversational applications
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Alan Nichol on building a suite of open source tools for chatbot developers. In this episode of the Data Show, I spoke with Alan Nichol, co-founder and CTO of Rasa, a startup that builds open source tools to help developersContinue reading “Using machine learning to improve dialog flow in conversational applications”
Building a natural language processing library for Apache Spark
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: David Talby on a new NLP library for Spark, and why model development starts after a model gets deployed to production. When I first discovered and started using Apache Spark, a majority of the use cases I used it forContinue reading “Building a natural language processing library for Apache Spark”
Language understanding remains one of AI’s grand challenges
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: David Ferrucci on the evolution of AI systems for language understanding. Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. InContinue reading “Language understanding remains one of AI’s grand challenges”
Natural language analysis using Hierarchical Temporal Memory
[A version of this post appears on the O’Reilly Radar.] The O’Reilly Data Show Podcast: Francisco Webber on building HTM-based enterprise applications. Subscribe to the O’Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. In this episode of theContinue reading “Natural language analysis using Hierarchical Temporal Memory”
Topic Models: Past, Present, Future
[A version of this post appears on the O’Reilly Radar blog.] The O’Reilly Data Show Podcast: David Blei, co-creator of one of the most popular tools in text mining and machine learning. I don’t remember when I first came across topic models, but I do remember being an early proponent of them in industry. IContinue reading “Topic Models: Past, Present, Future”