IBM Big Data Hub

FEBRUARY 13, 2024

Generative AI represents a significant advancement in deep learning and AI development, with some suggesting it’s a move towards developing “ strong AI.” Project management and operations : Generative AI tools can support project managers with automation within their platforms.

Enterprise 120

Enterprise Modeling Testing Data-driven 120

O'Reilly on Data

DECEMBER 12, 2019

1] This includes C-suite executives, front-line data scientists, and risk, legal, and compliance personnel. These recommendations are based on our experience, both as a data scientist and as a lawyer, focused on managing the risks of deploying ML. 2] The Security of Machine Learning. [3] Sensitivity analysis.

Machine Learning 187

Machine Learning Modeling Testing Risk Management 187

Smart Data Collective

MAY 8, 2022

Above all, there needs to be a set methodology for data mining, collection, and structure within the organization before data is run through a deep learning algorithm or machine learning. Identifying risks. Bg data has been very responsive in responding to risk management by providing new solutions.

Big Data 105

Big Data Data Analytics Analytics Cost-Benefit 105

Ontotext

FEBRUARY 26, 2024

The answers to these foundational questions help you uncover opportunities and detect risks. We bundle these events under the collective term “Risk and Opportunity Events” This post is part of Ontotext’s AI-in-Action initiative aimed to empower data, scientists, architects and engineers to leverage LLMs and other AI models.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

Smart Data Collective

DECEMBER 9, 2021

The role of accountants is changing to reflect this, with many accountants focusing on analyzing data and gleaning insights from that data , in order to increase efficiency and perform better risk management. Deep learning has been especially useful for small business accounting.

Technology 122

Technology Big Data Machine Learning Deep Learning 122

CIO Business Intelligence

MARCH 13, 2024

L’analisi dei dati attraverso l’apprendimento automatico (machine learning, deep learning, reti neurali) è la tecnologia maggiormente utilizzata dalle grandi imprese che utilizzano l’IA (51,9%). Le reti neurali sono il modello di machine learning più utilizzato oggi. Perché l’IA Generativa è così “importante”?

Machine Learning 95

Machine Learning Deep Learning Big Data Testing 95

IBM Big Data Hub

MAY 17, 2024

But as businesses around the globe rapidly adopt the technology to augment processes from merchandising to order management, there is some risk. Inventory transparency and order accuracy AI-powered order management systems provide real-time visibility into all aspects of the critical order management workflow.

B2B 66

B2B Interactive Optimization Forecasting 66

DataRobot Blog

MARCH 7, 2023

Your AI teams will be equipped with self-serve tools, explainable automation, and manual overrides to run hundreds of diverse models in minutes, allowing you to solve business problems faster with less risk to the business. The capability to rapidly build an AI-powered organization with industry-specific solutions and expertise.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

DataRobot Blog

SEPTEMBER 13, 2022

These might include—but are not limited to—deep learning, image recognition and natural language processing. As the internal footprint of AI increases, teams need to secure proper model governance to mitigate risk in compliance with regulations. Sometimes, even a simple linear regression might do the trick.

Forecasting 52

Forecasting Data-driven Machine Learning Optimization 52

IBM Big Data Hub

AUGUST 28, 2023

Machine learning algorithms like Naïve Bayes and support vector machines (SVM), and deep learning models like convolutional neural networks (CNN) are frequently used for text classification. Crisis management and risk management: Text mining serves as an invaluable tool for identifying potential crises and managing risks.

Data mining 54

Data mining Machine Learning Deep Learning Marketing 54

BizAcuity

MARCH 31, 2022

85% of AI (marketing) projects fail due to risk, confusion, and lack of upskilling among marketing teams.(Source: Not just banking and financial services, but many organizations use big data and AI to forecast revenue, exchange rates, cryptocurrencies and certain macroeconomic variables for hedging purposes and risk management.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

DataRobot Blog

DECEMBER 20, 2022

The use of artificial intelligence (AI) in the investment sector is proving to be a significant disruptor, catalyzing the connection between the different players and delivering a more vivid picture of the future risk and opportunities across all different market segments. Real estate investments are not an exception.

Management 59

Management Machine Learning Optimization Modeling 59

BizAcuity

APRIL 6, 2022

Hence, a lot of time and effort should be invested into research and development, hedging and risk management. To predict movements and volatility, machine learning and deep learning algorithms are widely used by organizations to strategize and prepare accordingly.

Data Analytics 52

Data Analytics Analytics B2B Deep Learning 52

Domino Data Lab

APRIL 3, 2019

Also, while surveying the literature two key drivers stood out: Risk management is the thin-edge-of-the-wedge ?for We find ways to improve machine learning so that it requires orders of magnitude more data, e.g., deep learning with neural networks. Moreover, one team manages the entire lifecycle for all ?customer

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84