Applied Data Science

JANUARY 4, 2022

Hiding your 2021 resolution list under a glass of champagne? To write this post we shook the internet upside down for industry news and research breakthroughs and settled on the following 5 themes, to wrap up 2021 in a neat bow: ? In 2021, the following were added to the ever growing list of Transformer applications.

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Artificial Intelligence Artificial Intelligence Neural Network Deep Learning 52

IBM Journey to AI blog

AUGUST 1, 2023

The term “foundation model” was coined by the Stanford Institute for Human-Centered Artificial Intelligence in 2021. A foundation model is built on a neural network model architecture to process information much like the human brain does. An open-source model, Google created BERT in 2018.

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Generative AI BERT Data Scientist Machine Learning 189

Mlearning.ai

JUNE 14, 2023

Learning LLMs (Foundational Models) Base Knowledge / Concepts: What is AI, ML and NLP Introduction to ML and AI — MFML Part 1 — YouTube What is NLP (Natural Language Processing)? — YouTube YouTube Introduction to Natural Language Processing (NLP) NLP 2012 Dan Jurafsky and Chris Manning (1.1)

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Neural Network BERT Large Language Models Natural Language Processing 52

AWS Machine Learning Blog

FEBRUARY 6, 2024

In 2021, the pharmaceutical industry generated $550 billion in US revenue. Traditional manual processing of adverse events is made challenging by the increasing amount of health data and costs. BERT can be fine-tuned for a variety of NLP tasks, including question answering, natural language inference, and sentiment analysis.

Large Language Models 119

Large Language Models BERT NLP Data Scientist 119

Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. Evolution of NLP Models To understand the full impact of the above evolutionary process.

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NLP Neural Network Natural Language Processing Convolutional Neural Networks 98

Towards AI

JULY 20, 2023

Natural Language Processing Getting desirable data out of published reports and clinical trials and into systematic literature reviews (SLRs) — a process known as data extraction — is just one of a series of incredibly time-consuming, repetitive, and potentially error-prone steps involved in creating SLRs and meta-analyses.

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Data Extraction NLP Natural Language Processing Automation 75

Snorkel AI

MARCH 1, 2023

This process results in generalized models capable of a wide variety of tasks, such as image classification, natural language processing, and question-answering, with remarkable accuracy. BERT proved useful in several ways, including quantifying sentiment and predicting the words likely to follow in unfinished sentences.

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BERT Natural Language Processing Large Language Models Neural Network 83

Sebastian Ruder

NOVEMBER 14, 2022

Models that allow interaction via natural language have become ubiquitious. Research models such as BERT and T5 have become much more accessible while the latest generation of language and multi-modal models are demonstrating increasingly powerful capabilities. Named entity annotations in African languages in MasakhaNER.

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics BERT 52

ML @ CMU

FEBRUARY 24, 2023

Prompting has emerged as a promising approach to solving a wide range of NLP problems using large pre-trained language models (LMs), including left-to-right models such as GPT s and masked LMs such as BERT , RoBERTa , etc. BERT and GPTs) for both classification and generation tasks. Webson and Pavlick (2021) , Zhao et al.,

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BERT NLP Large Language Models Natural Language Processing 100

The Stanford AI Lab Blog

MAY 31, 2022

Language Model Pretraining Language models (LMs), like BERT 1 and the GPT series 2 , achieve remarkable performance on many natural language processing (NLP) tasks. To achieve this, we first chunk each document into segments of roughly 256 tokens, which is half of the maximum BERT LM input length.

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BERT Natural Language Processing NLP Neural Network 40

DataRobot Blog

FEBRUARY 2, 2023

These developments have allowed researchers to create models that can perform a wide range of natural language processing tasks, such as machine translation, summarization, question answering and even dialogue generation. writefile $BASE_PATH/custom.py """ Copyright 2021 DataRobot, Inc. pip install transformers==4.25.1

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BERT Large Language Models Natural Language Processing Machine Learning 52

NVIDIA Developer

MAY 20, 2021

Chung , posted May 21 2021 at 12:03AM Businesses worldwide are using artificial intelligence to solve their greatest challenges. In this workshop, you’ll learn how deep learning works through hands-on exercises in computer vision and natural language processing.

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Natural Language Processing Deep Learning Neural Network NLP 40

Sebastian Ruder

DECEMBER 6, 2021

This post expands on the EMNLP 2021 tutorial on Multi-domain Multilingual Question Answering. Reading Comprehension assumes a gold paragraph is provided Standard approaches for reading comprehension build on pre-trained models such as BERT. The tutorial was organised by Avi Sil and me. The slides are available online.

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BERT NLP Natural Language Processing Computational Linguistics 52

Sebastian Ruder

FEBRUARY 24, 2021

Fine-tuning a pre-trained language model (LM) has become the de facto standard for doing transfer learning in natural language processing. 2018 ) while pre-trained language models are favoured over models trained on translation ( McCann et al., 2018 ), natural language inference ( Conneau et al.,

Natural Language Processing 52

Natural Language Processing BERT NLP Computer Vision 52

Viso.ai

FEBRUARY 25, 2023

Transformer models have become the de-facto status quo in Natural Language Processing (NLP). For example, the popular ChatGPT AI chatbot is a transformer-based language model. They are based on the transformer architecture, which was originally proposed for natural language processing (NLP) in 2017.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

Viso.ai

JUNE 12, 2024

Their applications include various Natural Language Processing ( NLP ) tasks, including question answering, text summarization, sentiment analysis , etc. Previous ChatGPT models The GPT-1 version was introduced in June 2018 as a method for language understanding by using generative pre-training.

Large Language Models 52

Large Language Models ChatGPT Computer Vision Neural Network 52

Topbots

JULY 6, 2023

In the rapidly evolving field of artificial intelligence, natural language processing has become a focal point for researchers and developers alike. However, unlike most language models, LaMDA was trained on dialogue to pick up on nuances that distinguish open-ended conversation from other forms of language.

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LLM Large Language Models Natural Language Processing OpenAI 52

John Snow Labs

JUNE 5, 2023

Sentence detection is an essential component in many natural language processing (NLP) tasks, as it enables the analysis of text at a more granular level by breaking it down into individual sentences. Sentence Detection in Spark NLP is the process of automatically identifying the boundaries of sentences in a given text.

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NLP Natural Language Processing Deep Learning Algorithm 52

Heartbeat

AUGUST 2, 2023

Large language models, such as GPT-3 (Generative Pre-trained Transformer 3), BERT, XLNet, and Transformer-XL, etc., Overall, transformer architecture has revolutionized the field of natural language processing by enabling efficient and effective modeling of long-range dependencies and capturing complex contextual relationships in text.

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Large Language Models Prompt Engineer Prompt Engineering OpenAI 52

Snorkel AI

MARCH 8, 2023

The agenda today is to first learn how to build a unified foundation model, which is a unit paper from ICCV (International Conference on Computer Vision) 2021. By modalities I mean, specifically, NLP (natural language processing) or computer vision, and also the domains which require the combination of both of them.

NLP 52

NLP BERT Computer Vision Natural Language Processing 52

Snorkel AI

MARCH 8, 2023

The agenda today is to first learn how to build a unified foundation model, which is a unit paper from ICCV (International Conference on Computer Vision) 2021. By modalities I mean, specifically, NLP (natural language processing) or computer vision, and also the domains which require the combination of both of them.

NLP 52

NLP BERT Computer Vision Natural Language Processing 52

DataRobot Blog

MARCH 9, 2022

The company was acquired by DataRobot in 2021. This is one of the reasons why detecting sentiment from natural language (NLP or natural language processing ) is a surprisingly complex task. This article was originally published at Algorithimia’s website. Find out more about DataRobot MLOps here.

Machine Learning 52

Machine Learning Neural Network Convolutional Neural Networks Deep Learning 52

Sebastian Ruder

JANUARY 19, 2021

The selection of areas and methods is heavily influenced by my own interests; the selected topics are biased towards representation and transfer learning and towards natural language processing (NLP). Powerful multilingual models that cover around 100 languages emerged including XML-R ( Conneau et al., 2020 ; Rust et al.,

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NLP ML Computer Vision Neural Network 52

Applied Data Science

DECEMBER 23, 2022

In our review of 2019 we talked a lot about reinforcement learning and Generative Adversarial Networks (GANs), in 2020 we focused on Natural Language Processing (NLP) and algorithmic bias, in 202 1 Transformers stole the spotlight. The debate was on again: maybe language generation is really just a prediction task?

Neural Network 52

Neural Network Data Science AI AI 52

Chatbots Life

MAY 12, 2023

In practice, we can ask a language model to continue the sequence with the word it thinks is the most probable. The most recent training data is of ChatGPT from 2021 September. About the author Hello, my name is Aleksander Obuchowski, I am passionate about Natural Language Processing and AI in Medicine.

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ChatGPT Software Engineer NLP Prompt Engineer 105

deepsense.ai

NOVEMBER 14, 2023

Within Natural Language Processing (NLP), ‘pseudo-evaluation’ approaches that we call ‘Superficial Utility Comparison Kriterion’ ( SUCK ) methods, like BLEU [32], METEOR [33], ROUGE [34], or BLEURT [35], attempt to salvage the situation. 2023 [link] [link] [link] BERTScore: Evaluating text generation with BERT , Zhang T.,

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Generative AI Prompt Engineer Prompt Engineering ML 111

AWS Machine Learning Blog

SEPTEMBER 12, 2023

By implementing a modern natural language processing (NLP) model, the response process has been shaped much more efficiently, and waiting time for clients has been reduced tremendously. In 2021, Scalable Capital experienced a tenfold increase of its client base, from tens of thousands to hundreds of thousands.

Data Scientist 122

Data Scientist Data Science NLP Machine Learning 122

Topbots

JUNE 29, 2023

4] In the open-source camp, initial attempts at solving the Text2SQL puzzle were focussed on auto-encoding models such as BERT, which excel at NLU tasks.[5, Content Enhanced BERT-based Text-to-SQL Generation [8] Torsten Scholak et al. Speak to your Parser: Interactive Text-to-SQL with Natural Language Feedback [16] Janna Lipenkova.

Auto-complete 52

Auto-complete Algorithm Data Scientist Auto-classification 52

Topbots

JUNE 6, 2023

Autoencoding models, which are better suited for information extraction, distillation and other analytical tasks, are resting in the background — but let’s not forget that the initial LLM breakthrough in 2018 happened with BERT, an autoencoding model. We’ll let you know when we release more summary articles like this one.

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LLM ChatGPT Prompt Engineer Prompt Engineering 102