Analytics Vidhya

JULY 27, 2023

Introduction A highly effective method in machine learning and natural language processing is topic modeling. A corpus of text is an example of a collection of documents. This technique involves finding abstract subjects that appear there.

Natural Language Processing 271

Natural Language Processing Machine Learning Machine Learning Analytics 271

Flipboard

APRIL 23, 2025

Traditional keyword-based search mechanisms are often insufficient for locating relevant documents efficiently, requiring extensive manual review to extract meaningful insights. This solution improves the findability and accessibility of archival records by automating metadata enrichment, document classification, and summarization.

AWS 107

AWS ML ML AI 107

Dataconomy

APRIL 30, 2025

Intelligent document processing (IDP) is transforming the way businesses manage their documentation and data management processes. By harnessing the power of emerging technologies, organizations can automate the extraction and handling of data from various document types, significantly enhancing operational workflows.

Natural Language Processing 91

Natural Language Processing Machine Learning Machine Learning ML 91

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.

Natural Language Processing 105

Natural Language Processing Machine Learning Machine Learning Python 105

AWS Machine Learning Blog

MAY 15, 2025

The banking industry has long struggled with the inefficiencies associated with repetitive processes such as information extraction, document review, and auditing. This substantial reduction in processing time not only accelerates workflows but also minimizes the risk of manual errors.

AWS 93

AWS ML ML Machine Learning 93

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.

AWS 149

AWS AI AI Machine Learning 149

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."

AI 370

AI AI Natural Language Processing Artificial Intelligence 370

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.

AWS 160

AWS Natural Language Processing Machine Learning Machine Learning 160

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.

AWS 154

AWS ML ML Machine Learning 154

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.

Natural Language Processing 369

Natural Language Processing Deep Learning Deep Learning Predictive Analytics 369

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.

Exploratory Data Analysis 111

Exploratory Data Analysis EDA Data Analysis Data Analysis 111

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.

Machine Learning 136

Machine Learning Machine Learning Supervised Learning Algorithm 136

Flipboard

JANUARY 9, 2025

In India, the KYC verification usually involves identity verification through identification documents for Indian citizens, such as a PAN card or Aadhar card, address verification, and income verification. They have developed a solution that fully automates the customer onboarding, KYC verification, and credit underwriting process.

AWS 160

AWS Machine Learning Machine Learning AI 160

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.

Azure 52

Azure Machine Learning Machine Learning Data Science 52

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.

AWS 115

AWS ML ML Machine Learning 115

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.

Data Scientist 195

Data Scientist Natural Language Processing Machine Learning Machine Learning 195

AWS Machine Learning Blog

DECEMBER 17, 2024

This new capability from Amazon Bedrock offers a unified experience for developers of all skillsets to easily automate the extraction, transformation, and generation of relevant insights from documents, images, audio, and videos to build generative AI powered applications.

AWS 112

AWS AI AI Python 112

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.

AWS 117

AWS AI AI Machine Learning 117

AWS Machine Learning Blog

NOVEMBER 13, 2024

By taking advantage of advanced natural language processing (NLP) capabilities and data analysis techniques, you can streamline common tasks like these in the financial industry: Automating data extraction – The manual data extraction process to analyze financial statements can be time-consuming and prone to human errors.

AWS 117

AWS AI AI Natural Language Processing 117

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.

AWS 120

AWS Natural Language Processing ML ML 120

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.

Machine Learning 129

Machine Learning Machine Learning ML ML 129

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.

AWS 133

AWS Natural Language Processing AI AI 133

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.

AWS 167

AWS Clustering Artificial Intelligence Artificial Intelligence 167

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.

Machine Learning 369

Machine Learning Machine Learning Natural Language Processing ML 369

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.

Machine Learning 195

Machine Learning Machine Learning Natural Language Processing Algorithm 195

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.

AWS 117

AWS AI AI Data Scientist 117

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.

AWS 127

AWS Python ML ML 127

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.

Natural Language Processing 211

Natural Language Processing Machine Learning Machine Learning Data Science 211

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.

Database 140

Database AWS ML ML 140

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.

AI 100

AI AI Machine Learning Machine Learning 100

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.

Natural Language Processing 85

Natural Language Processing AI AI Machine Learning 85

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.

AWS 65

AWS ML ML Machine Learning 65

Flipboard

MAY 1, 2025

Mortgage processing is a complex, document-heavy workflow that demands accuracy, efficiency, and compliance. Recent industry surveys indicate that only about half of borrowers express satisfaction with the mortgage process, with traditional banks trailing non-bank lenders in borrower satisfaction. Why agentic IDP?

AWS 153

AWS AI AI Cross Validation 153

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.

AWS 117

AWS AI AI Data Scientist 117

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.

Natural Language Processing 170

Natural Language Processing Machine Learning Machine Learning AI 170

Flipboard

JUNE 3, 2025

Understanding the challenge Enterprise knowledge bases contain vast repositories of informationfrom documentation and policies to technical guides and product specifications. Traditional search approaches are often inadequate when users ask natural language questions, failing to understand context or identify the most relevant content.

AWS 141

AWS AI AI Database 141

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"

ML 103

ML ML Python AWS 103