IBM Journey to AI blog

AUGUST 28, 2023

These are two common methods for text representation: Bag-of-words (BoW): BoW represents text as a collection of unique words in a text document. Term frequency-inverse document frequency (TF-IDF): TF-IDF calculates the importance of each word in a document based on its frequency or rarity across the entire dataset.

Data Mining 170

Data Mining Convolutional Neural Networks Categorization Machine Learning 170

AWS Machine Learning Blog

MAY 24, 2023

In this three-part series, we present a solution that demonstrates how you can automate detecting document tampering and fraud at scale using AWS AI and machine learning (ML) services for a mortgage underwriting use case. Fraudsters range from blundering novices to near-perfect masters when creating fraudulent loan application documents.

Automation 81

Automation Computer Vision Data Extraction IDP 81

Unite.AI

SEPTEMBER 16, 2024

Key Features: Real-time data replication and integration with major data warehouses. Cons: Confusing transformations, lack of pipeline categorization, view sync issues. It also offers EDI management features alongside data governance. Key Features: Cloud-native platform with powerful data migration capabilities.

Data Integration 170

Data Integration ETL Big Data Automation 170

John Snow Labs

SEPTEMBER 17, 2024

Healthcare Data Abstraction: The Three Barriers To begin with, each project has its own sets of rules for what, how, and when data should be extracted and normalized. Second, the information is frequently derived from natural language documents or a combination of structured, imaging, and document sources.

NLP 52

NLP Natural Language Processing Categorization Automation 52

Unite.AI

SEPTEMBER 16, 2024

Key Features: Real-time data replication and integration with major data warehouses. Cons: Confusing transformations, lack of pipeline categorization, view sync issues. Visit Hevo Data → 7. It also offers EDI management features alongside data governance. Visit SAP Data Services → 10. Visit Boomi → 8.

Data Integration 170

Data Integration ETL Big Data Automation 170

Flipboard

OCTOBER 25, 2023

Text, images, audio, and videos are common examples of unstructured data. Most companies produce and consume unstructured data such as documents, emails, web pages, engagement center phone calls, and social media. Understanding the data, categorizing it, storing it, and extracting insights from it can be challenging.

ML 166

ML Metadata Data Extraction AI 166

Unite.AI

JULY 26, 2024

AI-powered automation systems can handle tedious tasks such as filling out forms, scheduling meetings, and managing documentation. In the accounts payable department, AI can benefit payment processing, invoice capture, data extraction, invoice workflow automation , and even fraud detection.

Automation 130

Automation AI AI Categorization 130

Marktechpost

AUGUST 17, 2024

Although substantial research has identified and categorized these risks, a unified framework is needed to be consistent with terminology and clarity. Two taxonomies were developed: the Causal Taxonomy, categorizing risks by responsible entity, intent, and timing, and the Domain Taxonomy, classifying risks into specific domains.

Categorization 64

Categorization AI AI Data Extraction 64

AWS Machine Learning Blog

AUGUST 1, 2024

Challenges in document understanding for underwriting Document understanding is a critical and complex aspect of the underwriting process that poses significant challenges for insurers. This is a complex task when faced with unstructured data, varying document formats, and erroneous data.

Generative AI 119

Generative AI Natural Language Processing Machine Learning AI 119

John Snow Labs

JANUARY 30, 2025

Biomarker Analysis and Relationship Extraction: Biomarkers play a pivotal role in modern oncology, serving as indicators for diagnosis, prognosis, and treatment response. Relation extraction is used to connect biomarkers to their respective results, enabling a detailed understanding of the role biomarkers play in cancer diagnosis.

NLP 52

NLP Large Language Models LLM Data Analysis 52

Marktechpost

AUGUST 4, 2023

Features include real-time OCR data extraction from invoices, bills, and receipts, automatic transaction categorization, and AI-assisted reconciliation. Documents can be managed in bulk, discrepancies can be found and fixed, and dynamic reports can be generated.

AI Tools 98

AI Tools Artificial Intelligence Artificial Intelligence Automation 98

AWS Machine Learning Blog

MAY 7, 2024

Tasks such as routing support tickets, recognizing customers intents from a chatbot conversation session, extracting key entities from contracts, invoices, and other type of documents, as well as analyzing customer feedback are examples of long-standing needs. In this example, you explicitly set the instance type to ml.g5.48xlarge.

Prompt Engineer 115

Prompt Engineer Prompt Engineering Large Language Models LLM 115

Kavita Ganesan

JULY 28, 2022

Document Segmentation Problem 13. Keyword Extraction 14. Classification A classification problem is about assigning one or more categories to a document, product, person, or image—essentially anything. One of the goals of information extraction is to fill templates using data extracted from raw text.

AI 52

AI AI Categorization Data Extraction 52

Mlearning.ai

MARCH 15, 2023

In this article, we will cover the third & fourth sections i.e. Data Extraction, Preprocessing & EDA & Machine Learning Model development Data collection : Automatically download the stock historical prices data in CSV format and save it to the AWS S3 bucket. Please refer to this documentation link.

Python 52

Python Machine Learning Data Extraction Data Analysis 52

Marktechpost

DECEMBER 12, 2024

These documents, which detail a drugs indications, risks, and clinical trial results, are critical but time-consuming to curate, often exceeding 100 pages per drug. The model categorized toxicity using ternary (No, Less, Most) and binary (Yes, No) scales.

Large Language Models 43

Large Language Models Categorization Data Extraction Machine Learning 43

John Snow Labs

MAY 24, 2023

Developing a machine learning model requires a big amount of training data. Therefore, the data needs to be properly labeled/categorized for a particular use case. Companies can use high-quality human-powered data annotation services to enhance ML and AI implementations.

Natural Language Processing 52

Natural Language Processing NLP Machine Learning Auto-classification 52

Pickl AI

JULY 10, 2023

These packages allow for text preprocessing, sentiment analysis, topic modeling, and document classification. It allows data scientists to combine code, documentation, and visualizations in a single document, making it easier to share and reproduce analyses.

Data Science 52

Data Science Data Scientist Machine Learning Data Analysis 52

John Snow Labs

JANUARY 30, 2025

Dataset For this benchmark, we utilized 48 open-source documents annotated by domain experts from John Snow Labs. Launched in 2024, the service offers three key operations: Tag, Redact, and Surrogate, enabling healthcare organizations to process diverse types of clinical documents securely and efficiently.

NLP 52

NLP Natural Language Processing Large Language Models Machine Learning 52

John Snow Labs

JANUARY 30, 2025

Dataset For this benchmark, we utilized 48 open-source documents annotated by domain experts from John Snow Labs. Launched in 2024, the service offers three key operations: Tag, Redact, and Surrogate, enabling healthcare organizations to process diverse types of clinical documents securely and efficiently.

OpenAI 52

OpenAI NLP Large Language Models Natural Language Processing 52

Dlabs.ai

DECEMBER 6, 2022

Sounds crazy, but Wei Shao (Data Scientist at Hortifrut) and Martin Stein (Chief Product Officer at G5) both praised the solution. launched an initiative called ‘ AI 4 Good ‘ to make the world a better place with the help of responsible AI.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Computer Vision Machine Learning 52

Viso.ai

AUGUST 20, 2024

Machine Learning model training over a decentralized network – Source Secure Data sharing by using Blockchain Data owners can contribute their datasets to the decentralized AI model training without actually moving the data off their premises.

AI Modeling 52

AI Modeling AI AI Machine Learning 52

AWS Machine Learning Blog

NOVEMBER 26, 2024

Task 1: Query generation from natural language This task’s objective is to assess a model’s capacity to translate natural language questions into SQL queries, using contextual knowledge of the underlying data schema. We use real incident data from Sophos’s MDR for incident summarization.

LLM 92

LLM Machine Learning ML Prompt Engineer 92

Viso.ai

MARCH 29, 2024

Here are these: Data Preprocessing: The first step involves collecting the data (usually scrapped from the internet). Then pre-processing the semi-structured data to transform it into noise-free documents ready for further analysis and knowledge extraction. scientists, artists).

ML 40

ML Deep Learning NLP BERT 40

AWS Machine Learning Blog

JANUARY 7, 2025

Machine learning (ML) classification models offer improved categorization, but introduce complexity by requiring separate, specialized models for classification, entity extraction, and response generation, each with its own training data and contextual limitations. Built-in conditional logic handles different processing paths.

Generative AI 98

Generative AI Automation Data Extraction ETL 98