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 53

Data mining Machine Learning Deep Learning Marketing 53

bridgei2i

OCTOBER 7, 2020

To get a perspective on evolving trends in insurance in the post-COVID world, read BRIDGEi2i’s blog here. Underwriting is a process that involves extraction & collation of information about the insured from different sources in structured & unstructured format. (if click here. Challenges in underwriting.

Insurance 52

Insurance Sales Strategy Digital Transformation 52

Domino Data Lab

AUGUST 9, 2021

Before selecting a tool, you should first know your end goal – machine learning or deep learning. Machine learning identifies patterns in data using algorithms that are primarily based on traditional methods of statistical learning. It’s most helpful in analyzing structured data.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. .

Testing 300

Testing Machine Learning Consulting Data Quality 300

Sisense

MAY 26, 2020

In Talking Data , we delve into the rapidly evolving worlds of Natural Language Processing and Generation. Text data is proliferating at a staggering rate, and only advanced coding languages like Python and R will be able to pull insights out of these datasets at scale. Today, text data is everywhere.

Unstructured Data 98

Unstructured Data Big Data Testing Machine Learning 98

IBM Big Data Hub

JANUARY 10, 2024

AI operates on three fundamental components: data, algorithms and computing power. 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.

Unstructured Data 76

Unstructured Data Deep Learning Cost-Benefit Machine Learning 76

Domino Data Lab

AUGUST 10, 2021

Models are the central output of data science, and they have tremendous power to transform companies, industries, and society. At the center of every machine learning or artificial intelligence application is the ML/AI model that is built with data, algorithms and code. It’s used for developing deep learning models.

Modeling 64

Modeling IT Risk Management Deep Learning 64

IBM Big Data Hub

AUGUST 1, 2023

It’s the underlying engine that gives generative models the enhanced reasoning and deep learning capabilities that traditional machine learning models lack. That’s where the foundation model enters the picture. They can also quickly and accurately translate marketing collateral into multiple languages.

Modeling 55

Modeling Cost-Benefit Data Lake Machine Learning 55

Ontotext

MAY 22, 2023

This is the case with the so-called intelligent data processing (IDP), which uses a previous generation of machine learning. Luckily, the text analysis that Ontotext does is focused on tasks that require complex domain knowledge and linking of documents to reference data or master data.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

DataRobot

NOVEMBER 9, 2021

When we convert the single channel audio signal time series into an energy spectrogram, it allows us to run state of the art deep learning architectures on the image. . Spectrograms are not the only transformations available to convert signal data to images. Image courtesy towardsAI. See DataRobot in Action.

Visualization 52

Visualization Unstructured Data Statistics Metrics 52

datapine

NOVEMBER 19, 2019

An important part of artificial intelligence comprises machine learning, and more specifically deep learning – that trend promises more powerful and fast machine learning. An exemplary application of this trend would be Artificial Neural Networks (ANN) – the predictive analytics method of analyzing data.

Technology 279

Technology Internet of Things IT IoT 279

Ontotext

FEBRUARY 26, 2024

Using machine learning, RED indicates the impact of events on stock prices. It compares actual price changes to expected changes based on historical data. This semantic model serves as a blueprint or framework against which raw data is analyzed and organized. Let’s have a quick look under the bonnet.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

IBM Big Data Hub

MAY 17, 2023

The services are activated through access management for data collection, analysis and event monitoring in existing drones which are managed by clients and businesses. The flexibility of DaaS in offering a multiplicity of data collection services for different industry use cases makes it unique.

Data Collection 77

Data Collection Visualization Data-driven Unstructured Data 77