IBM Journey to AI blog

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. Data extraction Once you’ve assigned numerical values, you will apply one or more text-mining techniques to the structured data to extract insights from social media data.

Convolutional Neural Networks 144

Convolutional Neural Networks Data Mining Categorization Machine Learning 144

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. Prodigy offers the support in the paid version.

Natural Language Processing 52

Natural Language Processing NLP Machine Learning Auto-classification 52

AWS Machine Learning Blog

MAY 7, 2024

Whether you’re looking to classify documents, extract keywords, detect and redact personally identifiable information (PIIs), or parse semantic relationships, you can start ideating your use case and use LLMs for your natural language processing (NLP). Intents are categorized into two levels: main intent and sub intent.

Prompt Engineer 95

Prompt Engineer Prompt Engineering Large Language Models LLM 95

Flipboard

OCTOBER 25, 2023

Why it’s challenging to process and manage unstructured data Unstructured data makes up a large proportion of the data in the enterprise that can’t be stored in a traditional relational database management systems (RDBMS). Understanding the data, categorizing it, storing it, and extracting insights from it can be challenging.

ML 132

ML Metadata AI AI 132

ODSC - Open Data Science

OCTOBER 27, 2023

The core idea behind this phase is automating the categorization or classification using AI. We will specifically focus on the two most common uses: template-based normalized key-value entity extractions and document Q&A, with large language models.

IDP 98

IDP LLM Large Language Models AI 98

Pickl AI

JULY 10, 2023

R’s machine learning capabilities allow for model training, evaluation, and deployment. · Text Mining and Natural Language Processing (NLP): R offers packages such as tm, quanteda, and text2vec that facilitate text mining and NLP tasks. It literally has all of the technologies required for machine learning jobs.

Data Science 52

Data Science Data Scientist Data Analysis Machine Learning 52

Viso.ai

MARCH 29, 2024

It represents the most common form of data and includes examples such as images, videos, audio, and PDF files. Unstructured data preprocessing is more complex and can involve text cleaning, and feature extraction. NLP libraries (such as SpaCy) and various machine learning algorithms are used to process this type of data.

ML 52

ML Deep Learning NLP BERT 52