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Understanding Transformers: A Deep Dive into NLP’s Core Technology

Analytics Vidhya

Introduction Welcome into the world of Transformers, the deep learning model that has transformed Natural Language Processing (NLP) since its debut in 2017. These linguistic marvels, armed with self-attention mechanisms, revolutionize how machines understand language, from translating texts to analyzing sentiments.

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Understanding and coding Neural Networks From Scratch in Python and R

Analytics Vidhya

Note: This article was originally published on May 29, 2017, and updated on July 24, 2020 Overview Neural Networks is one of the most. The post Understanding and coding Neural Networks From Scratch in Python and R appeared first on Analytics Vidhya.

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The limitations of deep learning (2017)

Hacker News

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Transformers Revolutionized AI. What Will Replace Them?

Flipboard

If modern artificial intelligence has a founding document, a sacred text, it is Google’s 2017 research paper “Attention Is All You Need.” This paper introduced a new deep learning architecture known as the transformer, which has gone on to revolutionize the field of AI over the past half-decade.

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Test your Data Science Skills on Transformers library

Analytics Vidhya

A team at Google Brain developed Transformers in 2017, and they are now replacing RNN models like long short-term memory(LSTM) as the model of choice for NLP […]. This article was published as a part of the Data Science Blogathon. The post Test your Data Science Skills on Transformers library appeared first on Analytics Vidhya.

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What Is a Transformer Model?

Hacker News

First described in a 2017 paper from Google, transformers are among the newest and one of the most powerful classes of models invented to date. They’re driving a wave of advances in machine learning some have dubbed transformer AI. Now we see self-attention is a powerful, flexible tool for learning,” he added. “Now

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Who is Durk Kingma, Anthropic’s latest transfer from OpenAI?

Dataconomy

cum laude in machine learning from the University of Amsterdam in 2017. His academic work, particularly in deep learning and generative models, has had a profound impact on the AI community. He earned his Ph.D.