NLP

Listening is everything—especially when it comes to effective marketing and product design. Gain key market insights from social media data using sentiment analysis and topic modeling in Python.

Colloquial language doesn’t lend itself to computation. That’s where natural language processing steps in. Learn how topic modeling helps computers understand human speech.

Pre-trained models are making waves in the deep learning world. Using massive pre-training datasets, these NLP models bring previously unheard-of feats of AI within the reach of app developers.

For a successful natural language processing project, collecting and preparing data, building resilient pipelines, and getting "model ready" can easily take months of effort even with the most talented engineers. But what if we could reduce the data required to a fraction? In this article, we’ll cover how transfer learning is making world-class models open source and introduce BERT (bidirectional encoder representations from transformers). BERT is the most powerful NLP “tool” to date. We’ll explore how it works and why it will change the way companies execute NLP projects.

Natural language processing (NLP) has become one of the most researched subjects in the field of AI. This interest is driven by applications that have been brought to market in recent years. In this article, Toptal Deep Learning Developer Maximilian Hopf introduces you to Google’s Natural Language API and Google AutoML Natural Language.

Manually gathering information about user-generated data is time-consuming, to say the least. That's why more organizations are turning to automatic sentiment analysis methods—but basic models don't always cut it. In this article, Toptal Freelance Data Scientist Rudolf Eremyan gives an overview of some sentiment analysis gotchas and what can be done to address them.

Deep learning has proven its power across many domains, from beating humans at complex board games to synthesizing music. It has also been used extensively in natural language processing. In this article, Toptal Freelance Software Engineer Shanglun (Sean) Wang shows how easy it is to build a text classification program using different techniques and how well they perform against each other.

Natural language is increasingly becoming a viable way of interacting with smart software. Google search, Apple’s Siri, Microsoft’s Cortana, etc. are all capable of understanding queries in natural language. In this article, Toptal Freelance Software Engineer Shanglun (Sean) Wang walks us through some useful concepts and techniques in natural language processing and shows how they can be used to build a simple NLP app.