Hacker News

AUGUST 12, 2024

In this paper we present a new method for automatic transliteration and segmentation of Unicode cuneiform glyphs using Natural Language Processing (NLP) techniques. Cuneiform is one of the earliest known writing system in the world, which documents millennia of human civilizations in the ancient Near East.

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Flipboard

DECEMBER 3, 2024

As a global leader in agriculture, Syngenta has led the charge in using data science and machine learning (ML) to elevate customer experiences with an unwavering commitment to innovation. Efficient metadata storage with Amazon DynamoDB – To support quick and efficient data retrieval, document metadata is stored in Amazon DynamoDB.

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AWS AI AI Machine Learning 149

Towards AI

DECEMBER 28, 2023

10+ Python packages for Natural Language Processing that you can’t miss, along with their corresponding code.Foto di Max Duzij su Unsplash Natural Language Processing is the field of Artificial Intelligence that involves text analysis. It combines statistics and mathematics with computational linguistics.

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Natural Language Processing Python Machine Learning Machine Learning 105

Data Science Dojo

JULY 22, 2023

In the field of software development, generative AI is already being used to automate tasks such as code generation, bug detection, and documentation. Bug detection: OpenAI’s machine learning models can be used to detect bugs and errors in code. Prompt: "Generate documentation for the following function."

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Flipboard

NOVEMBER 20, 2024

By narrowing down the search space to the most relevant documents or chunks, metadata filtering reduces noise and irrelevant information, enabling the LLM to focus on the most relevant content. This approach narrows down the search space to the most relevant documents or passages, reducing noise and irrelevant information.

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How to Learn Machine Learning

MAY 2, 2025

Welcome to this comprehensive guide on Azure Machine Learning , Microsoft’s powerful cloud-based platform that’s revolutionizing how organizations build, deploy, and manage machine learning models. This is where Azure Machine Learning shines by democratizing access to advanced AI capabilities.

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Azure Machine Learning Machine Learning Data Science 52

Flipboard

FEBRUARY 11, 2025

Large-scale data ingestion is crucial for applications such as document analysis, summarization, research, and knowledge management. These tasks often involve processing vast amounts of documents, which can be time-consuming and labor-intensive. The Process Data Lambda function redacts sensitive data through Amazon Comprehend.

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Data Science Dojo

JULY 2, 2023

Over the past few years, a shift has shifted from Natural Language Processing (NLP) to the emergence of Large Language Models (LLMs). Transformers, a type of Deep Learning model, have played a crucial role in the rise of LLMs.

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Towards AI

NOVEMBER 6, 2024

Unlocking efficient legal document classification with NLP fine-tuning Image Created by Author Introduction In today’s fast-paced legal industry, professionals are inundated with an ever-growing volume of complex documents — from intricate contract provisions and merger agreements to regulatory compliance records and court filings.

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Dataconomy

AUGUST 31, 2023

Classification in machine learning involves the intriguing process of assigning labels to new data based on patterns learned from training examples. Machine learning models have already started to take up a lot of space in our lives, even if we are not consciously aware of it.

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Data Science Dojo

JUNE 10, 2024

Here are some key ways data scientists are leveraging AI tools and technologies: 6 Ways Data Scientists are Leveraging Large Language Models with Examples Advanced Machine Learning Algorithms: Data scientists are utilizing more advanced machine learning algorithms to derive valuable insights from complex and large datasets.

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AWS Machine Learning Blog

NOVEMBER 25, 2024

This is significant for medical professionals who need to process millions to billions of patient notes without straining computing budgets. You can try out the models with SageMaker JumpStart, a machine learning (ML) hub that provides access to algorithms, models, and ML solutions so you can quickly get started with ML.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

Principal wanted to use existing internal FAQs, documentation, and unstructured data and build an intelligent chatbot that could provide quick access to the right information for different roles. As Principal grew, its internal support knowledge base considerably expanded.

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Flipboard

DECEMBER 6, 2023

Tools like LangChain , combined with a large language model (LLM) powered by Amazon Bedrock or Amazon SageMaker JumpStart , simplify the implementation process. Implementation includes the following steps: The first step is to break down the large document, such as a book, into smaller sections, or chunks.

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Data Science Dojo

SEPTEMBER 10, 2024

LLM companies are businesses that specialize in developing and deploying Large Language Models (LLMs) and advanced machine learning (ML) models. It has also risen as a dominant player in the LLM space, leading the changes within the landscape of natural language processing and AI-driven solutions.

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Data Science Dojo

AUGUST 17, 2023

Embeddings are a key building block of large language models. They are used to represent words as vectors of numbers, which can then be used by machine learning models to understand the meaning of text. This can make it difficult for machine learning models to learn the correct meaning of words.

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AWS Machine Learning Blog

JUNE 12, 2024

In today’s data-driven business landscape, the ability to efficiently extract and process information from a wide range of documents is crucial for informed decision-making and maintaining a competitive edge. Confidence scores and human review Maintaining data accuracy and quality is paramount in any document processing solution.

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AWS Machine Learning Blog

NOVEMBER 10, 2023

In the recent past, using machine learning (ML) to make predictions, especially for data in the form of text and images, required extensive ML knowledge for creating and tuning of deep learning models. These capabilities include pre-trained models for image, text, and document data types.

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AWS Machine Learning Blog

MARCH 17, 2025

Large language models (LLMs) have revolutionized the field of natural language processing, enabling machines to understand and generate human-like text with remarkable accuracy. However, despite their impressive language capabilities, LLMs are inherently limited by the data they were trained on.

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Dataconomy

APRIL 17, 2025

Prerequisite of training your AI: Where marketing strategy meets machine learning How to train AI across different marketing channels? AI in marketing refers to the use of machine learning (ML), natural language processing (NLP), and predictive analytics to automate, optimize, and personalize campaigns at scale.

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DrivenData Labs

MAY 18, 2023

I work on machine learning for natural language processing, and I’m particularly interested in few-shot learning, lifelong learning, and societal and health applications such as abuse detection, misinformation, mental ill-health detection, and language assessment. Data science is a broad field.

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AWS Machine Learning Blog

MARCH 21, 2025

Research papers and engineering documents often contain a wealth of information in the form of mathematical formulas, charts, and graphs. Navigating these unstructured documents to find relevant information can be a tedious and time-consuming task, especially when dealing with large volumes of data.

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AWS Machine Learning Blog

OCTOBER 24, 2023

In today’s information age, the vast volumes of data housed in countless documents present both a challenge and an opportunity for businesses. Traditional document processing methods often fall short in efficiency and accuracy, leaving room for innovation, cost-efficiency, and optimizations.

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IBM Data Science in Practice

JANUARY 2, 2025

Healthcare system faces persistent challenges due to its heavy reliance on manual processes and fragmented communication. Providers struggle with the administrative burden of documentation and coding, which consumes 2531% of total healthcare spending and detracts from their ability to deliver quality care.

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Flipboard

JANUARY 6, 2025

After completion of the program, Precise achieved Advanced tier partner status and was selected by a federal government agency to create a machine learning as a service (MLaaS) platform on AWS. The platform helped the agency digitize and process forms, pictures, and other documents.

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AWS Machine Learning Blog

JANUARY 8, 2024

AWS customers in healthcare, financial services, the public sector, and other industries store billions of documents as images or PDFs in Amazon Simple Storage Service (Amazon S3). In this post, we focus on processing a large collection of documents into raw text files and storing them in Amazon S3.

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Flipboard

MARCH 1, 2023

The new age focus uses natural language processing to help businesses create more effective marketing messages. Its platform can analyze customer data and generate language that resonates with specific audiences. Its platform uses machine learning to analyze ad data and provide insights and recommendations.

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AWS Machine Learning Blog

OCTOBER 26, 2023

Enterprises seek to harness the potential of Machine Learning (ML) to solve complex problems and improve outcomes. Canvas users select the index where their documents are, and can ideate, research, and explore knowing that the output will always be backed by their sources-of-truth.

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AWS Machine Learning Blog

OCTOBER 29, 2024

For a detailed breakdown of the features and implementation specifics, refer to the comprehensive documentation in the GitHub repository. You can follow the steps provided in the Deleting a stack on the AWS CloudFormation console documentation to delete the resources created for this solution.

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Dataconomy

MARCH 21, 2025

Key components include machine learning, which allows systems to learn from data, and natural language processing, enabling machines to understand and respond to human language. Legal: AI improves document analysis, streamlining legal research.

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AWS Machine Learning Blog

NOVEMBER 1, 2023

Organizations can search for PII using methods such as keyword searches, pattern matching, data loss prevention tools, machine learning (ML), metadata analysis, data classification software, optical character recognition (OCR), document fingerprinting, and encryption.

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Data Science Dojo

DECEMBER 6, 2023

GPT-4 with Vision combines natural language processing capabilities with computer vision. It could be a game-changer in digitizing written or printed documents by converting images of text into a digital format. Object Detection GPT-4V has superior object detection capabilities.

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Flipboard

JANUARY 14, 2025

Moreover, interest in small language models (SLMs) that enable resource-constrained devices to perform complex functionssuch as natural language processing and predictive automationis growing. These documents are chunked by the application and are sent to the embedding model.

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AWS Machine Learning Blog

FEBRUARY 6, 2025

Extracts of AEP documentation, describing each Measure type covered, its input and output types, and how to use it. An in-context learning technique that includes semantically relevant solved questions and answers in the prompt. About the Authors Javier Beltrn is a Senior Machine Learning Engineer at Aetion.

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AWS Machine Learning Blog

DECEMBER 12, 2024

In this two-part series, we introduce the abstracted layer of the SageMaker Python SDK that allows you to train and deploy machine learning (ML) models by using the new ModelTrainer and the improved ModelBuilder classes. For the detailed list of pre-set values, refer to the SDK documentation. amazonaws.com/pytorch-training:2.0.0-cpu-py310"

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ML ML Python AWS 94

Flipboard

AUGUST 25, 2023

Ever-growing volumes of unstructured data stored in countless document formats significantly complicate data processing and timely access to relevant …

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AWS Machine Learning Blog

APRIL 29, 2025

The following example shows how prompt optimization converts a typical prompt for a summarization task on Anthropics Claude Haiku into a well-structured prompt for an Amazon Nova model, with sections that begin with special markdown tags such as ## Task, ### Summarization Instructions , and ### Document to Summarize.

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