Unite.AI

JULY 28, 2023

MarketMuse, founded by Aki Balogh and Jeff Coyle in 2013, is a content marketing and keyword planner tool that utilizes artificial intelligence and machine learning. Conducts real-time research with NLP, semantic analysis, and the best SEO practices to write an entire article. MarketMuse Key Features: Competitive content analysis.

AI 246

AI AI Artificial Intelligence Artificial Intelligence 246

Towards AI

APRIL 8, 2024

While numerous techniques have been explored, methods harnessing natural language processing (NLP) have demonstrated strong performance. Word2Vec, a widely-adopted NLP algorithm has proven to be an efficient and valuable tool that is now applied across multiple domains, including recommendation systems.

Natural Language Processing 81

Natural Language Processing NLP Neural Network Algorithm 81

AWS Machine Learning Blog

JANUARY 4, 2024

One such area that is evolving is using natural language processing (NLP) to unlock new opportunities for accessing data through intuitive SQL queries. Instead of dealing with complex technical code, business users and data analysts can ask questions related to data and insights in plain language.

Prompt Engineer 141

Prompt Engineer Prompt Engineering Generative AI LLM 141

Mlearning.ai

APRIL 1, 2023

NLP A Comprehensive Guide to Word2Vec, Doc2Vec, and Top2Vec for Natural Language Processing In recent years, the field of natural language processing (NLP) has seen tremendous growth, and one of the most significant developments has been the advent of word embedding techniques.

Deep Learning 52

Deep Learning NLP Natural Language Processing Neural Network 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). 2020 ) and language modelling ( Khandelwal et al., In NLP, Gunel et al. 2020 ; Lewis et al.,

NLP 52

NLP ML Computer Vision Neural Network 52

Viso.ai

OCTOBER 9, 2024

to uncontrolled environments (SFEW, FER-2013, etc.). Comparison of State-of-the-art methods for AI emotion analysis There is a common discrepancy in accuracy when testing in controlled environment databases compared to wild environment databases. For example , a model obtaining 98.9% Get a demo for your organization.

Convolutional Neural Networks 98

Convolutional Neural Networks Neural Network Computer Vision Emotion AI 98

Topbots

JUNE 15, 2023

Language Disparity in Natural Language Processing This digital divide in natural language processing (NLP) is an active area of research. 2 ] Multilingual models perform worse on several NLP tasks on low resource languages than on high resource languages such as English.[

Natural Language Processing 59

Natural Language Processing Computational Linguistics NLP ChatGPT 59

AWS Machine Learning Blog

FEBRUARY 2, 2024

Embeddings capture the information content in bodies of text, allowing natural language processing (NLP) models to work with language in a numeric form. In entered the Big Data space in 2013 and continues to explore that area. He also holds an MBA from Colorado State University.

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ETL DevOps LLM Generative AI 128

Lexalytics

APRIL 5, 2021

Fast-forward a couple of decades: I was (and still am) working at Lexalytics, a text-analytics company that has a comprehensive NLP stack developed over many years. This is the sort of representation that is useful for natural language processing. I was out of the neural net biz. and BERT.

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

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. They are now the foundation of today’s NLP systems. Let’s use LinkBERT! LinkBERT improves previous BERT models on many applications.

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BERT Natural Language Processing NLP Neural Network 40

ML Review

FEBRUARY 26, 2018

Following its successful adoption in computer vision and voice recognition, DL will continue to be applied in the domain of natural language processing (NLP). ACM, 2013: 2333–2338. [2] 2] Minghui Qiu and Feng-Lin Li. MeChat: A Sequence to Sequence and Rerank based Chatbot Engine.

Robotics 52

Robotics Deep Learning Chatbots Machine Learning 52

Probably Approximately a Scientific Blog

AUGUST 30, 2019

This has caused some fear among the general population; some criticism among other NLP people; and many questions from their relatives ("hey, look at this article I've found - did they just solve NLP? While I might be late to the dangerous language models party, I thought this blog lacks a basic post about text generation.

NLP 52

NLP BERT OpenAI Natural Language Processing 52

Hal Daumé III

AUGUST 14, 2016

P16-1152 : Artem Sokolov; Julia Kreutzer; Christopher Lo; Stefan Riezler Learning Structured Predictors from Bandit Feedback for Interactive NLP This was perhaps my favorite paper of the conference because it's trying to do something new and hard and takes a nice approach. P16-2096 : Dirk Hovy; Shannon L.

Neural Network 40

Neural Network Natural Language Processing NLP 40

Sebastian Ruder

OCTOBER 26, 2019

Cross-lingual learning might be useful—but why should we care about applying NLP to other languages in the first place? The Digital Language Divide The language you speak shapes your experience of the world. Note that many languages cannot be assigned clearly to a single level of the hierarchy.

BERT 52

BERT NLP Natural Language Processing Neural Network 52

Bugra Akyildiz

NOVEMBER 17, 2024

Vision Transformers(ViT) ViT is a type of machine learning model that applies the transformer architecture, originally developed for natural language processing, to image recognition tasks. and 8B base and chat models, supporting both English and Chinese languages. 2020) EBM : Explainable Boosting Machine (Nori, et al.

Convolutional Neural Networks 52

Convolutional Neural Networks Metadata Computer Vision Python 52

Sebastian Ruder

DECEMBER 6, 2021

RC Olympics: The many domains of reading comprehension Datasets in the Fiction domain typically require processing narratives in books such as NarrativeQA ( Kočiský et al., 2013 ), MCScript ( Modi et al., The MLQA alignment and annotation process ( Lewis et al., 2018 ), Children's Book Test ( Hill et al.,

BERT 52

BERT NLP Natural Language Processing Computational Linguistics 52

Explosion

DECEMBER 17, 2013

I wrote this blog post in 2013, describing an exciting advance in natural language understanding technology. Natural languages introduce many unexpected ambiguities, which our world-knowledge immediately filters out. The derivation for the transition system we’re using, Arc Hybrid, is in Goldberg and Nivre (2013).

Python 45

Python Algorithm NLP Computational Linguistics 45

Topbots

SEPTEMBER 11, 2023

3] Don Norman (2013). 4] Google, Gartner and Motista (2013). Continuous Discovery Habits: Discover Products that Create Customer Value and Business Value. [2] 2] Orbit Media (2022). New Blogging Statistics: What Content Strategies Work in 2022? We asked 1016 Bloggers. [3] The Design of Everyday Things. [4]

UX Design 59

UX Design AI AI Automation 59

Artificial Corner

JUNE 6, 2023

Natural Language Processing (NLP) techniques can be applied to analyze and understand unstructured text data. MapReduce: simplified data processing on large clusters. The integration of AI and ML into data engineering pipelines enables a wide range of applications. Zaharia, M., O’Neil, E., & Chen, X.

Data Mining 52

Data Mining Big Data ETL Machine Learning 52

ML Review

JUNE 4, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part Two) This is the second instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). Attention and Memory in Deep Learning and NLP.

Neural Network 52

Neural Network Convolutional Neural Networks Computer Vision Deep Learning 52

Probably Approximately a Scientific Blog

JANUARY 3, 2016

We're already after 6 posts on the topic of natural language processing, and I can't believe I haven't discussed this basic topic yet. So today I'm going to discuss words; More accurately - I will discuss how words are represented in natural language processing. CoRR, 2013. Distributional structure."

Natural Language Processing 52

Natural Language Processing Algorithm Deep Learning NLP 52

ML Review

MAY 3, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part One) This is the first instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). Thanks for reading!

Neural Network 52

Neural Network Computer Vision Deep Learning Convolutional Neural Networks 52

NLP People

JULY 24, 2019

We took the opportunity to review major research trends in the animated NLP space and formulate some implications from the business perspective. The article is backed by a statistical and – guess what – NLP-based analysis of ACL papers from the last 20 years. But what is the substance behind the buzz?

NLP 52

NLP Neural Network Deep Learning Natural Language Processing 52

ODSC - Open Data Science

FEBRUARY 29, 2024

The Stanford AI Lab Founded in 1963, the Stanford AI Lab has made significant contributions to various domains, including natural language processing, computer vision, and robotics. Recently, they unveiled new mind-body neural control prostheses. Another project, SynthID , helps to identify and watermark AI-generated images.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence AI Research AI Researcher 52

Viso.ai

DECEMBER 21, 2023

His doctoral thesis studied the design of convolutional/recurrent neural networks and their applications across computer vision, natural language processing, and their intersections. His contributions to ML, deep learning , computer vision, and NLP underscore his influence in the rapidly evolving AI landscape.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 52

Probably Approximately a Scientific Blog

NOVEMBER 12, 2016

In the my introductory post about NLP I introduced the following survey question: when you search something in Google (or any other search engine of your preference), is your query: (1) a full question, such as "What is the height of Mount Everest?" (2) In EMNLP 2013. [3] Question answering systems have been around since the 1960s.

NLP 52

NLP Natural Language Processing 52

Probably Approximately a Scientific Blog

NOVEMBER 23, 2016

Antonymy in NLP While there is a vast linguistics literature about antonyms, I'm less familiar with it, and I'm going to focus on some observations and interesting points about antonymy that appear in NLP papers that I read. ACL 2015. [3] 3] Computing Word-Pair Antonymy. Saif Mohammad, Bonnie Dorr and Graeme Hirst. EMNLP 2008. [4]

NLP 52

NLP Natural Language Processing Categorization 52