From customization to scalability, there’s a lot to consider when deciding whether to build or buy an NLP or system. In this article we outline the dilemma and explore the pros and cons and costs of both options.
BERT Explained: Next-Level Natural Language Processing
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BERT is the latest and greatest in Natural Language Processing technology. Our VP of Marketing, Andrea Kulkarni, stops by the blog to explain what it is and how it impacts Lexalytics.
Sentiment Accuracy: Explaining the Baseline and How to Test It
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3 m
How accurate can we get with automated sentiment analysis through natural language processing? Let’s run a quick test and see what we learn.
Cloud or On Premise for Data Analytics: How to Choose
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5 m
These 4 factors are driving big names back to private cloud or on premise implementations for data storage and analytics. Should you move, too?
Machine Learning Micromodels: More Data is Not Always Better
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6 m
Machine learning micromodels reduce the challenges of sourcing and annotating data while delivering better precision and accuracy than macromodels.
The Ultimate NLP Tuning FAQ: Sentiment, Topics and More
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11 m
Lexalytics Support Engineer Sarah Williams answers our users’ most frequently-asked questions about how to tune Lexalytics’ natural language processing.
The World’s First On-Premise SaaS Text Analytics System
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4 m
Our Semantria SaaS text analytics API can now be deployed wherever you need depending on your privacy, security and scalability requirements.
Context Analysis in NLP: Why It’s Valuable and How It’s Done
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12 m
Context analysis in NLP involves extracting n-grams, noun phrases, themes, and facets. This article explains the value of context and how we extract it.
Natural Language Processing in 5 Minutes
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4 m
What is natural language processing? And what does it mean for you, me and your drunk friend? Seth Redmore explains the fundamental concepts of NLP in 5 minutes or fewer.
Hyperparameter Theft!
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4 m
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!
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