Bert

Natural Language Processing

Domain-specific Language Model Pretraining for Biomedical Natural Language Processing

Microsoft Research presents this talk on pretraining large neural language models, such as BERT, has led to impressive gains on many natural language processing (NLP) tasks.  However, most pretraining efforts focus on general-domain corpora, such as in newswire and web text. Biomedical text is very different from general-domain text, yet biomedical NLP has been relatively […]

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Natural Language Processing

NVIDIA Is Streamlining Natural Language Processing Development with Jarvis

Machine Learning with Phil explains how one of the big hurdles to rapid deployment of natural language processing applications is the lack of access to a fully integrated pipeline and state of the art models. Nvidia’s Jarvis Jarvis solves both problems by including everything you need to start developing enterprise grade solutions in a single […]

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Natural Language Processing Spark

Advanced Natural Language Processing with Apache Spark NLP

NLP is a key component in many data science systems that must understand or reason about text. This hands-on tutorial uses the open-source Spark NLP library to explore advanced NLP in Python. Spark NLP provides state-of-the-art accuracy, speed, and scalability for language understanding by delivering production-grade implementations of some of the most recent research in […]

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AI Research

Explaining the Paper: Hopfield Networks is All You Need

Yannic Kilcher explains the paper “Hopfield Networks is All You Need.” Hopfield Networks are one of the classic models of biological memory networks. This paper generalizes modern Hopfield Networks to continuous states and shows that the corresponding update rule is equal to the attention mechanism used in modern Transformers. It further analyzes a pre-trained BERT […]

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AI Natural Language Processing

GPT-3: Language Models are Few-Shot Learners

How far can you go with ONLY language modeling? Can a large enough language model perform NLP task out of the box? OpenAI take on these and other questions by training a transformer that is an order of magnitude larger than anything that has ever been built before and the results are astounding. Yannic Kilcher […]

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Natural Language Processing

Natural Language Processing, GPT-2 and BERT

Christoph Henkelmann (DIVISIO) explains what sets Google’s natural language processing model BERT apart from other language models, how can a custom version version be implemented and what is the so-called ImageNetMoment?

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AI Natural Language Processing

Pretrained Deep Bidirectional Transformers (BERT) for Language Understanding

Here’s a talk by Danny Luo Pre-training of Deep Bidirectional Transformers for Language Understanding We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers. Unlike recent language representation models, BERT is designed to pre-train deep bidirectional representations by jointly conditioning on both left and right context in all […]

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How To Build A BERT Classifier Model With TensorFlow 2.0
Natural Language Processing TensorFlow

How To Build A BERT Classifier Model With TensorFlow 2.0

BERT is one of the most popular algorithms in the NLP spectrum known for producing state-of-the-art results in a variety of language modeling tasks. Built on top of transformers and seq-to-sequence models, the Bidirectional Encoder Representations from Transformers is a powerful NLP modeling technique that sits at the cutting edge. Here’s a great write up […]

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Natural Language Processing

Language Learning with BERT

Martin Andrews talks about the basics of BERT for NLP at the TensorFlow and Deep Learning Singapore Meetup. Event Page: https://www.meetup.com/TensorFlow-and-Deep-Learning-Singapore/events/256431012/

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AI Natural Language Processing

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Yannic Kilcher investigates BERT and the white paper associated with it https://arxiv.org/abs/1810.04805 Abstract:We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers. Unlike recent language representation models, BERT is designed to pre-train deep bidirectional representations by jointly conditioning on both left and right context in all layers. As […]

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