ODSC - Open Data Science

JUNE 9, 2023

2000–2015 The new millennium gave us low-rise jeans, trucker hats, and bigger advancements in language modeling, word embeddings, and Google Translate. 2015 and beyond — Word2vec, GloVe, and FASTTEXT Word2vec, GloVe, and FASTTEXT focused on word embeddings or word vectorization. or ChatGPT (2022) ChatGPT is also known as GPT-3.5

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Data Science Dojo

SEPTEMBER 13, 2023

Deep learning And NLP Deep Learning and Natural Language Processing (NLP) are like best friends in the world of computers and language. Deep Learning is when computers use their brains, called neural networks, to learn lots of things from a ton of information.

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AWS Machine Learning Blog

JUNE 3, 2025

Amazon Simple Storage Service (Amazon S3) provides secure storage for conversation logs and supporting documents, and Amazon Bedrock powers the core natural language processing capabilities. In the process of implementation, we discovered that Anthropics Claude 3.5 Taras is an AWS Certified ML Engineer Associate.

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Eugene Yan

JUNE 21, 2025

In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 6162–76. RefChecker: Reference-Based Fine-Grained Hallucination Checker and Benchmark for Large Language Models.” © Eugene Yan 2015 - 2025 • Feedback • RSS [link] Feng, Song, Siva Sankalp Patel, Hui Wan, and Sachindra Joshi.

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ODSC - Open Data Science

MARCH 10, 2025

Over the past decade, data science has undergone a remarkable evolution, driven by rapid advancements in machine learning, artificial intelligence, and big data technologies. The Deep Learning Boom (20182019) Between 2018 and 2019, deep learning dominated the conference landscape.

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AWS Machine Learning Blog

OCTOBER 5, 2023

Before that, he worked on developing machine learning methods for fraud detection for Amazon Fraud Detector. He is passionate about applying machine learning, optimization, and generative AI techniques to various real-world problems. He focuses on developing scalable machine learning algorithms.

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ODSC - Open Data Science

JUNE 24, 2025

In the case of even a simple large language model (LLM) question and answer use case, traditional natural language processing (NLP) metrics fall short of judging whether the free text output conceptually matches that of what we expect.

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AWS Machine Learning Blog

AUGUST 11, 2023

Natural language processing (NLP) is the field in machine learning (ML) concerned with giving computers the ability to understand text and spoken words in the same way as human beings can. For this solution, we use the 2015 New Year’s Resolutions dataset to classify resolutions.

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Towards AI

FEBRUARY 14, 2023

It involves using machine learning algorithms to generate new data based on existing data. Cohere, a startup that specializes in natural language processing, has developed a reputation for creating sophisticated applications that can generate natural language with great accuracy.

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IBM Journey to AI blog

NOVEMBER 13, 2023

Kubernetes’s declarative, API -driven infrastructure has helped free up DevOps and other teams from manually driven processes so they can work more independently and efficiently to achieve their goals. And Kubernetes can scale ML workloads up or down to meet user demands, adjust resource usage and control costs.

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Google Research AI blog

MARCH 7, 2023

books, magazines, newspapers, forms, street signs, restaurant menus) so that they can be indexed, searched, translated, and further processed by state-of-the-art natural language processing techniques. words per image on average, which is more than 3x the density of TextOCR and 25x more dense than ICDAR-2015.

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AWS Machine Learning Blog

FEBRUARY 28, 2023

In today’s highly competitive market, performing data analytics using machine learning (ML) models has become a necessity for organizations. Use natural language processing (NLP) in Amazon HealthLake to extract non-sensitive data from unstructured blobs. Perform one-hot encoding with Amazon SageMaker Data Wrangler.

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Towards AI

JULY 23, 2023

In the first part of the series, we talked about how Transformer ended the sequence-to-sequence modeling era of Natural Language Processing and understanding. Semi-Supervised Sequence Learning As we all know, supervised learning has a drawback, as it requires a huge labeled dataset to train. In 2015, Andrew M.

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AWS Machine Learning Blog

NOVEMBER 9, 2023

Her research interests lie in Natural Language Processing, AI4Code and generative AI. In the past, she had worked on several NLP-based services such as Comprehend Medical, a medical diagnosis system at Amazon Health AI and Machine Translation system at Meta AI.

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DagsHub

JULY 25, 2024

Source: Author Introduction Deep learning, a branch of machine learning inspired by biological neural networks, has become a key technique in artificial intelligence (AI) applications. Deep learning methods use multi-layer artificial neural networks to extract intricate patterns from large data sets.

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Heartbeat

APRIL 23, 2023

One of the key components of chatbot development is natural language processing (NLP), which allows the bot to understand and respond to human language. SpaCy is a popular open-source NLP library developed in 2015 by Matthew Honnibal and Ines Montani, the founders of the software company Explosion.

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Snorkel AI

MARCH 1, 2023

Foundation Models (FMs), such as GPT-3 and Stable Diffusion, mark the beginning of a new era in machine learning and artificial intelligence. Foundation models are large AI models trained on enormous quantities of unlabeled data—usually through self-supervised learning. What is self-supervised learning?

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IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

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Pickl AI

AUGUST 22, 2024

Researchers and developers favour PyTorch for its flexibility and ease of use, accelerating the development and experimentation of Machine Learning models. In industry, it powers applications in computer vision, natural language processing, and reinforcement learning.

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AWS Machine Learning Blog

APRIL 25, 2024

The most common techniques used for extractive summarization are term frequency-inverse document frequency (TF-IDF), sentence scoring, text rank algorithm, and supervised machine learning (ML). Hurricane Patricia has been rated as a categor… Human: 23 October 2015 Last updated at 17:44 B… [{‘name’: meteor’, “value’: 0.102339181286549.

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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., Background The Markov Blanket Discovery (MBD) approach is a graphical model-based method used for feature selection and causal discovery in machine learning (Peng et al.,

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Snorkel AI

MAY 24, 2023

The Future of Data-centric AI virtual conference will bring together a star-studded lineup of expert speakers from across the machine learning, artificial intelligence, and data science field. chief data scientist, a role he held under President Barack Obama from 2015 to 2017. Patil served as the first U.S.

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Snorkel AI

MAY 24, 2023

The Future of Data-centric AI virtual conference will bring together a star-studded lineup of expert speakers from across the machine learning, artificial intelligence, and data science field. chief data scientist, a role he held under President Barack Obama from 2015 to 2017. Patil served as the first U.S.

Machine Learning 52

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AWS Machine Learning Blog

APRIL 18, 2023

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the field with their incredible abilities to generate text, analyze sentiment, translate languages, and much more.

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Explosion

NOVEMBER 9, 2016

Over the last six months, a powerful new neural network playbook has come together for Natural Language Processing. now features deep learning models for named entity recognition, dependency parsing, text classification and similarity prediction based on the architectures described in this post. 2015) Paragraph Vector 57.7

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ML Review

FEBRUARY 26, 2018

Launched in July 2015, AliMe is an IHCI-based shopping guide and assistant for e-commerce that overhauls traditional services, and improves the online user experience. Following its successful adoption in computer vision and voice recognition, DL will continue to be applied in the domain of natural language processing (NLP).

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Explosion

NOVEMBER 21, 2019

In 2016 we trained a sense2vec model on the 2015 portion of the Reddit comments corpus, leading to a useful library and one of our most popular demos. Try the new interactive demo to explore similarities and compare them between 2015 and 2019 sense2vec (Trask et. Interestingly, “to ghost” wasn’t very common in 2015.

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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 : Johnson et al. using Faster-RCNN[ 82 ].

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Heartbeat

AUGUST 21, 2023

ResNet is a deep CNN architecture developed by Kaiming He and his colleagues at Microsoft Research in 2015. It consists of up to 152 layers and uses a novel “residual block” architecture that allows the network to learn residual connections between layers.

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PyImageSearch

JANUARY 30, 2023

For example, they can scan test papers with the help of natural language processing (NLP) algorithms to detect correct answers and grade them accordingly. Further, by analyzing grades, the software can analyze where individual students are lacking and how they can improve the learning process.

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Chatbots Life

MARCH 17, 2023

The Open Source community subsequently gains interest and thus actively contributed to all sorts of research repositories which brings us the vast collection of machine learning models today. Simply put, GPTs are machine learning models based on the neural network architecture that mimics the human brain.

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Explosion

DECEMBER 28, 2019

Jan 28: Ines then joined the great lineup of Applied Machine Learning Days in Lausanne, Switzerland. Sofie has been involved with machine learning and NLP as an engineer for 12 years. Basically, it’s an at-a-glance look at how (quickly) language has changed over the past four years.

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AWS Machine Learning Blog

APRIL 18, 2023

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the field with their incredible abilities to generate text, analyze sentiment, translate languages, and much more.

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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! Source : Assael et al.

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Explosion

FEBRUARY 12, 2017

In this post, I’ll explain how to solve text-pair tasks with deep learning, using both new and established tips and technologies. The Quora dataset is an example of an important type of Natural Language Processing problem: text-pair classification. Angeli, Gabor; Potts, Christopher; Manning, Christopher D.

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Explosion

MAY 10, 2016

By late 2015 I had the machine learning, hash table, outer parsing loop, and most of the feature extraction as nogil functions. Conclusion Natural language processing (NLP) programs have some peculiar performance characterstics. You can see the inner class here.

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Explosion

FEBRUARY 18, 2015

spaCy is a new library for text processing in Python and Cython. I wrote it because I think small companies are terrible at natural language processing (NLP). To do great NLP, you have to know a little about linguistics, a lot about machine learning, and almost everything about the latest research.

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