NLP

Showing 1-4 of 4 results
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Full-stack NLP with React: Ionic vs Cordova vs React Native

by Shanglun Wang

JavaScript frameworks based on React can help you build a fast, reliable mobile app, but it’s not always easy to determine which framework is best for your project. Choosing the wrong framework can result in an app with slow and redundant code. JavaScript expert Sean Wang builds the same natural language processing mobile application using Cordova, Ionic, and React Native, then discusses the advantages and limitations of each.

25+ minute readContinue Reading
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Getting the Most Out of Pre-trained Models

by Nauman Mustafa

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.

10 minute readContinue Reading
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Accelerate with BERT: NLP Optimization Models

by Jesse Moore

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.

6 minute readContinue Reading
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Four Pitfalls of Sentiment Analysis Accuracy

by Rudolf Eremyan

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.

6 minute readContinue Reading

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