Cloudera

NOVEMBER 15, 2021

In terms of representation, data can be broadly classified into two types: structured and unstructured. Structured data can be defined as data that can be stored in relational databases, and unstructured data as everything else. The challenges of data. Data annotation. Data curation.

Unstructured Data 85

Unstructured Data Recreation/Entertainment Structured Data Reporting 85

IBM Big Data Hub

AUGUST 28, 2023

Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data.

Data mining 56

Data mining Machine Learning Deep Learning Marketing 56

IBM Big Data Hub

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

Deep Learning 59

Deep Learning Machine Learning Unstructured Data Modeling 59

IBM Big Data Hub

JANUARY 10, 2024

Data: AI systems learn and make decisions based on data, and they require large quantities of data to train effectively, especially in the case of machine learning (ML) models. For optimal performance, AI models should receive data from a diverse datasets (e.g.,

Unstructured Data 79

Unstructured Data Deep Learning Cost-Benefit Modeling 79

CIO Business Intelligence

MARCH 9, 2022

As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio.

Data Lake 115

Data Lake Unstructured Data Data Warehouse Data Quality 115

Domino Data Lab

MARCH 3, 2019

The first survey started as a simple exploration into mainstream adoption of machine learning (ML). What’s been the impact of using ML models on culture and organization? Who builds their models? We also used maturity , in other words how long had an enterprise organization been deploying ML models in production?

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

IBM Big Data Hub

AUGUST 15, 2023

To overcome these challenges will require a shift in many of the processes and models that businesses use today: changes in IT architecture, data management and culture. A common phrase you’ll hear around AI is that artificial intelligence is only as good as the data foundation that shapes it.

IT 78

IT Data Governance Modeling Cost-Benefit 78