DataKitchen

APRIL 13, 2021

Monte Carlo Data — Data reliability delivered. Data breaks. Observe, optimize, and scale enterprise data pipelines. . Validio — Automated real-time data validation and quality monitoring. . DataMo – Datmo tools help you seamlessly deploy and manage models in a scalable, reliable, and cost-optimized way.

Testing 307

Testing Machine Learning Consulting Data Quality 307

IBM Big Data Hub

FEBRUARY 14, 2024

By infusing AI into IT operations , companies can harness the considerable power of NLP, big data, and ML models to automate and streamline operational workflows, and monitor event correlation and causality determination. AI platforms can use machine learning and deep learning to spot suspicious or anomalous transactions.

Cost-Benefit 86

Cost-Benefit Insurance Unstructured Data Machine Learning 86

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

JULY 6, 2023

Python is the most common programming language used in machine learning. Machine learning and deep learning are both subsets of AI. Deep learning teaches computers to process data the way the human brain does. Deep learning algorithms are neural networks modeled after the human brain.

Machine Learning 57

Machine Learning Data Science Statistics Deep Learning 57

IBM Big Data Hub

AUGUST 28, 2023

Named entity recognition (NER): NER extracts relevant information from unstructured data by identifying and classifying named entities (like person names, organizations, locations and dates) within the text. A targeted approach will optimize the user experience and enhance an organization’s ROI.

Data mining 56

Data mining Machine Learning Deep Learning Marketing 56

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Scale the problem to handle complex data structures. A Program Synthesis Primer ” – Aws Albarghouthi (2017-04-24).

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

bridgei2i

OCTOBER 7, 2020

Sometimes due to excessive volume of data, an underwriter can get confused and is unable to measure risk appropriately. Importance of capturing market data for optimized pricing models. The more data an underwriter has at his disposal, the more accurately he will be able to assess risk. The way ahead for insurers.

Insurance 52

Insurance Sales Strategy Digital Transformation 52

datapine

AUGUST 14, 2019

Data science tools are used for drilling down into complex data by extracting, processing, and analyzing structured or unstructured data to effectively generate useful information while combining computer science, statistics, predictive analytics, and deep learning.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

datapine

NOVEMBER 19, 2019

There are a large number of tools used in AI, including versions of search and mathematical optimization, logic, methods based on probability and economics, and many others. 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

IBM Big Data Hub

JANUARY 10, 2024

Data is often divided into three categories: training data (helps the model learn), validation data (tunes the model) and test data (assesses the model’s performance). For optimal performance, AI models should receive data from a diverse datasets (e.g.,

Unstructured Data 81

Unstructured Data Deep Learning Cost-Benefit Modeling 81

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 99

Data Lake Unstructured Data Data Warehouse Data Quality 99

IBM Big Data Hub

AUGUST 1, 2022

As a company, we have been entrusted with organizing data on a national scale, made revolutionary progress in data storing technology and have exponentially advanced trustworthy AI using aggregated structured and unstructured data from both internal and external sources. . 2000 Deep Learning: .

Unstructured Data 52

Unstructured Data Deep Learning Data Quality Data Architecture 52

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. They can also quickly and accurately translate marketing collateral into multiple languages.

Modeling 58

Modeling Cost-Benefit Data Lake Machine Learning 58

IBM Big Data Hub

MAY 17, 2023

The data captured by the sensors and housed in the cloud flow into real-time monitoring for 24/7 visibility into your assets, enabling the Predictive Failure Model. DaaS uses built-in deep learning models that learn by analyzing images and video streams for classification.

Data Collection 80

Data Collection Visualization Data-driven Unstructured Data 80

CIO Business Intelligence

JANUARY 20, 2023

Blocking the move to a more AI-centric infrastructure, the survey noted, are concerns about cost and strategy plus overly complex existing data environments and infrastructure. Though experts agree on the difficulty of deploying new platforms across an enterprise, there are options for optimizing the value of AI and analytics projects. [2]

Analytics 128

Analytics Key Performance Indicator Unstructured Data IoT 128

Smart Data Collective

OCTOBER 13, 2021

There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. This is something that you can learn more about in just about any technology blog. We would like to talk about data visualization and its role in the big data movement.

Visualization 133

Visualization Cost-Benefit Big Data Prescriptive Analytics 133