Text analytics is a "machine learning hard" task. This white paper gives a 10,000 foot view of Lexalytics' use of machine learning.
What are they talking about? Learn how we use natural language processing to categorize and sort comments, reviews and other text documents.
Who are they talking about? Learn how we extract people, places, dates, companies, products, jobs, and titles from text documents.
This white paper is a useful primer on the fundamentals and mechanisms of Natural Language Processing (NLP).
Should you build your analytics solution from the ground up? Or, should you sign a licensing agreement with a vendor. This white paper explores both options.
See how our natural language processing and “words-first” machine learning combine in this overview of our full-stack business intelligence solution.
Machine learning toolkit for solving unique natural language problems that saves time and reduces costs for data scientists.
Our Chief Scientist, Paul Barba, introduces a paper from his fellow Lexalytics researchers. The subject matter details how machines might be taught to understand context within natural language.
Paul Barba sat visited premier data publication KD Nuggets to discuss the importance of maintaining AI models.
Recently, our Chief Scientist, Paul Barba, explained to Dataversity the perils of relying on a one-size-fits-all AI solution with specific examples from history.
Our CEO, Jeff Catlin, stopped over at Forbes to discuss exactly how businesses can use artificial intelligence to create real world value.
Discover the 4 factors driving companies back to private cloud or on premise for data storage and analytics, and learn whether you should, too.
EContent announced their 2018 Trendsetting Products! We’re honored to see Lexalytics AI Assembler, our latest product, mentioned on the list. Check out this article to see how AI Assembler will change the space.
The Cambridge Analytica Files have ripped open the conversation around data analytics, privacy, and marketing. In this probing and humorous article, our CMO shares his unique perspective as a marketing professional at a data analytics company.
Elon Musk put on his oracle hat at SXSW and offered another dire warning to humanity: AI is dangerous and it is coming for you. Our CMO, Seth Redmore, takes issue with this.
Popular media and hype cycles are leading us to expect radical changes and perfect results from artificial intelligence. But you don’t read perfectly, so why should your AI? In this blog, veteran CIO Carl Lambrecht explains when “good” is good enough for AI.
Hyperparameter optimization is akin to a secret ingredient in Willy Wonka’s Chocolate Factory. And, much like Arthur Slugworth, there are nefarious entities afoot in the machine learning community. In this article, Chief Scientist Paul Barba goes over the ins and outs of hyperparameter theft!