ODSC - Open Data Science

JUNE 13, 2023

billion in 2017 to 3.78 The average annual growth in social media consumers has been 230 million between 2017 and 2021. Social Media Analysis using Natural Language Processing Techniques. Jyotika has been working on Natural Language Processing and Social Media data for 8 years. billion in 2021.

Data Science 52

Data Science Natural Language Processing Python Machine Learning 52

Mlearning.ai

APRIL 10, 2023

3 feature visual representation of a K-means Algorithm. Essentially, the clustering algorithm is grouping data points together without any prior knowledge or guidance to discover hidden patterns or unusual data groupings without the need for human interference. 4, center_box=(20, 5)) model = OPTICS().fit(x)

Algorithm 52

Algorithm Machine Learning Data Analysis Deep Learning 52

Viso.ai

JANUARY 16, 2024

Traditional software operates based on predefined, linear rules and algorithms explicitly programmed by humans. The ANN utilizes a pair of music files, each with a natural language description, such as ‘happy’ or ‘sad.’ Traditional software operates on fixed algorithms directly coded by programmers.

Neural Network 52

Neural Network Computer Vision Categorization Algorithm 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. trillion words.

Large Language Models 52

Large Language Models ChatGPT Computer Vision Neural Network 52

AWS Machine Learning Blog

AUGUST 16, 2023

Our solution is based on the DINO algorithm and uses the SageMaker distributed data parallel library (SMDDP) to split the data over multiple GPU instances. The images document the land cover, or physical surface features, of ten European countries between June 2017 and May 2018. tif" --include "_B03.tif" tif" --include "_B04.tif"

Metadata 74

Metadata Data Scientist Generative AI Natural Language Processing 74

Marktechpost

SEPTEMBER 17, 2024

Large language models (LLMs) have seen remarkable success in natural language processing (NLP). Many methods have been developed to achieve comparable accuracy with reduced training costs like optimized algorithms, distributed architectures, and hardware acceleration.

Large Language Models 109

Large Language Models LLM NLP Deep Learning 109

Probably Approximately a Scientific Blog

SEPTEMBER 14, 2018

With machine learning increasingly automating many previously manual decision making processes, it’s time to reflect not only on the algorithms’ performances but also on the ethical issues involved. Here are some questions about ethical concerns: Fairness : are the outputs of our algorithms fair towards everyone?

Machine Learning 52

Machine Learning Algorithm Natural Language Processing Automation 52

PyImageSearch

JANUARY 2, 2023

Machine learning algorithms can also recognize patterns in DNA sequences and predict a patient’s probability of developing an illness. These algorithms can design potential drug therapies, identify genetic causes of disease, and help understand the mechanisms underlying gene expression.

Computer Vision 52

Computer Vision Deep Learning Neural Network Machine Learning 52

Probably Approximately a Scientific Blog

APRIL 13, 2018

Although Mark Zuckerberg denied this conspiracy theory in his senate hearing , I doubt that people would stop believing it whenever the ads algorithm surprises them. 1/5 — Vered Shwartz (@VeredShwartz) October 17, 2017 In that case I was amazed by the accuracy of the Quora digest emails I was getting.

Algorithm 40

Algorithm Natural Language Processing NLP AI 40

AssemblyAI

MARCH 21, 2023

Top 50 keywords in submitted research papers at ICLR 2022 ( source ) A recent bibliometric study systematically analysed this research trend, revealing an exponential growth of published research involving GNNs, with a striking +447% average annual increase in the period 2017-2019.

Neural Network 313

Neural Network Deep Learning AI AI 313

Unite.AI

OCTOBER 27, 2023

Stiglitz, will lead to the transformation of civilization (Stiglitz, 2017). All moral attitudes, feelings, and desires of such a “person” become derived from human intelligence (Uzhov, 2017). Such a symbiosis will involve cooperation between humans and “smart” machines, which, according to Nobel Prize-winning economist J.

Artificial Intelligence 182

Artificial Intelligence Artificial Intelligence Robotics Neural Network 182

Sebastian Ruder

NOVEMBER 14, 2022

Developing models that work for more languages is important in order to offset the existing language divide and to ensure that speakers of non-English languages are not left behind, among many other reasons. In Proceedings of NIPS 2017. Transfer learning in natural language processing. Shazeer, N.,

Natural Language Processing 52

Natural Language Processing NLP Computational Linguistics BERT 52

Sebastian Ruder

JUNE 6, 2022

The algorithm tokenizes a word by determining its longest substring in the vocabulary and then recursing on the remaining string until a certain number of recursive calls. Rather than choosing subwords that occur frequently in the multilingual pre-training data (which biases the model towards high-resource languages), Patil et al.

NLP 52

NLP Natural Language Processing Computational Linguistics Neural Network 52

Viso.ai

JULY 9, 2024

Diagram that illustrates the reinforcement learning process through agent-environment interaction and the constituent ranking algorithm. This process loops as the agent continues to learn. The agent takes an action to interact with the environment, which changes its state and leads to a potential reward or penalty.

Neural Network 52

Neural Network Computer Vision Convolutional Neural Networks Deep Learning 52

AssemblyAI

MAY 3, 2023

With these fairly complex algorithms often being described as “giant black boxes” in news and media, a demand for clear and accessible resources is surging. This concept is not exclusive to natural language processing, and has also been employed in other domains. The outcome is the so-called policy model.

Large Language Models 363

Large Language Models Neural Network LLM ChatGPT 363

AWS Machine Learning Blog

NOVEMBER 9, 2023

This retrieval can happen using different algorithms. Her research interests lie in Natural Language Processing, AI4Code and generative AI. She received her PhD from Virginia Tech in 2017. He received his PhD from University of Illinois at Urbana-Champaign in 2017.

Natural Language Processing 94

Natural Language Processing NLP Large Language Models LLM 94

John Snow Labs

MAY 18, 2023

Word embeddings are considered as a type of representation used in natural language processing (NLP) to capture the meaning of words in a numerical form. Word embeddings are used in natural language processing (NLP) as a technique to represent words in a numerical format.

NLP 52

NLP Machine Learning Python Algorithm 52

Mlearning.ai

MARCH 9, 2023

Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., Understanding the robustness of image segmentation algorithms to adversarial attacks is critical for ensuring their reliability and security in practical applications.

Computer Vision 52

Computer Vision Deep Learning Machine Learning Algorithm 52

Viso.ai

DECEMBER 10, 2023

An introduction The basic concepts and how it works Traditional and modern deep learning image recognition The best popular image recognition algorithms How to use Python for image recognition Examples and deep learning applications Popular image recognition software About: We provide the leading end-to-end computer vision platform Viso Suite.

Convolutional Neural Networks 98

Convolutional Neural Networks Computer Vision Neural Network Deep Learning 98

Explosion

AUGUST 1, 2019

Transformers and transfer-learning Natural Language Processing (NLP) systems face a problem known as the “knowledge acquisition bottleneck”. The priority of wordpiece tokenizers is to limit the vocabulary size, as vocabulary size is one of the key challenges facing current neural language models ( Yang et al.,

BERT 52

BERT NLP Neural Network Categorization 52

Lexalytics

APRIL 5, 2021

This would change in 1986 with the publication of “Parallel Distributed Processing” [ 6 ], which included a description of the backpropagation algorithm [ 7 ]. In retrospect, this algorithm seems obvious, and perhaps it was. We were definitely in a Kuhnian pre-paradigmatic period. It would not be the last time that happened.)

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 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. Popular image recognition algorithms include ResNet , VGG , YOLOv3 , and YOLOv7. Viso Suite provides end-to-end software for AI vision.

Convolutional Neural Networks 52

Convolutional Neural Networks Computer Vision Neural Network Natural Language Processing 52

Sebastian Ruder

JULY 31, 2020

Natural language processing (NLP) research predominantly focuses on developing methods that work well for English despite the many positive benefits of working on other languages. Most of the world's languages are spoken in Asia, Africa, the Pacific region and the Americas.

NLP 78

NLP Natural Language Processing Machine Learning ML 78

John Snow Labs

JUNE 14, 2023

Stopwords removal in natural language processing (NLP) is the process of eliminating words that occur frequently in a language but carry little or no meaning. Stopwords cleaning in Spark NLP is the process of removing stopwords from the text data. setInputCol("text").setOutputCol("document")

NLP 52

NLP Natural Language Processing Metadata Python 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.

NLP 52

NLP Natural Language Processing Deep Learning Algorithm 52

Flipboard

FEBRUARY 5, 2023

It’s a nudge from Duolingo , the popular language-learning app, whose algorithms know you’re most likely to do your 5 minutes of Spanish practice at this time of day. Around 2017, the company started to make a more focused investment in machine learning, and that’s when coauthors Brust and Bicknell joined the team.

Machine Learning 182

Machine Learning AI AI Algorithm 182

John Snow Labs

MAY 26, 2023

Sentence embeddings are a powerful tool in natural language processing that helps analyze and understand language. Transformers, a type of neural network architecture, are a popular method for generating these embeddings. " sentence_df = spark.createDataFrame([[sentence_0], [sentence_1], [sentence_2]]).toDF("text")

NLP 52

NLP BERT Natural Language Processing Deep Learning 52

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. It is based on GPT and uses machine learning algorithms to generate code suggestions as developers write.

BERT 83

BERT Natural Language Processing Large Language Models Neural Network 83

Sebastian Ruder

OCTOBER 26, 2019

To ensure that non-English language speakers are not left behind and at the same time to offset the existing imbalance, we need to apply our models to non-English languages. The NLP Resource Hierarchy In current machine learning, the amount of available training data is the main factor that influences an algorithm's performance.

BERT 52

BERT NLP Neural Network Natural Language Processing 52

John Snow Labs

JUNE 6, 2023

Many different transformer models have already been implemented in Spark NLP, and specifically for text classification, Spark NLP provides various annotators that are designed to work with pretrained language models. This sequence can be made up of text, as well as other types of data like audio, images, or time series.

BERT 52

BERT Python NLP 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).  Reinforcement learning algorithms have a multitude of practical implications ( Bellemare et al.,

NLP 52

NLP ML Computer Vision Neural Network 52

AWS Machine Learning Blog

SEPTEMBER 11, 2024

Thirdly, the presence of GPUs enabled the labeled data to be processed. In 2017, the landmark paper “ Attention is all you need ” was published, which laid out a new deep learning architecture based on the transformer. Parallel computing uses these multiple processing elements simultaneously to solve a problem.

ML 86

ML Deep Learning Algorithm Large Language Models 86

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). Source: Lu et al. 2016)[ 91 ] You et al.

Neural Network 52

Neural Network Convolutional Neural Networks Computer Vision Deep Learning 52

John Snow Labs

JUNE 7, 2023

Normalization refers to the process of converting text to a standard format, which can help improve the accuracy and efficiency of subsequent natural language processing (NLP) tasks. It is a configurable component that can be customized based on specific use cases and requirements.

NLP 52

NLP Natural Language Processing Metadata Python 52

Topbots

JANUARY 30, 2023

In the last couple of years, Large Language Models (LLMs) such as ChatGPT, T5 and LaMDA have developed amazing skills to produce human language. We are quick to attribute intelligence to models and algorithms, but how much of this is emulation, and how much is really reminiscent of the rich language capability of humans?

Large Language Models 52

Large Language Models Computational Linguistics LLM Natural Language Processing 52

John Snow Labs

MAY 25, 2023

Rule-based sentiment analysis in Natural Language Processing (NLP) is a method of sentiment analysis that uses a set of manually-defined rules to identify and extract subjective information from text data. Sentiment analysis is an automated process capable of understanding the feelings or opinions that underlie a text.

NLP 52

NLP Machine Learning Neural Network ML 52

Marek Rei

NOVEMBER 12, 2019

Below you will find short summaries of a number of different research papers published in the areas of Machine Learning and Natural Language Processing in the past couple of years (2017-2019). Improving Neural Language Models with a Continuous Cache Edouard Grave, Armand Joulin, Nicolas Usunier. ArXiv 2017.

Machine Learning 52

Machine Learning NLP Neural Network BERT 52