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.

Machine Learning 105

Machine Learning Deep Learning Big Data Testing 105

IBM Big Data Hub

DECEMBER 15, 2023

Morgan’s Athena uses Python-based open-source AI to innovate risk management. Similarly, online educational platforms like Coursera and edX use open-source AI to personalize learning experiences, tailor content recommendations and automate grading systems.

Deep Learning 64

Deep Learning Experimentation Machine Learning Risk 64

DataRobot Blog

MARCH 7, 2023

Organizations that want to prove the value of AI by developing, deploying, and managing machine learning models at scale can now do so quickly using the DataRobot AI Platform on Microsoft Azure. AI Platform Single-Tenant SaaS are fully managed by DataRobot and replace disparate machine learning tools, simplifying management.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

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.” Generative AI uses advanced machine learning algorithms and techniques to analyze patterns and build statistical models.

Enterprise 118

Enterprise Testing Modeling Data-driven 118

Domino Data Lab

APRIL 3, 2019

That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Plus, the more mature machine learning (ML) practices place greater emphasis on these kinds of solutions than the less experienced organizations. for DG adoption in the enterprise.

Machine Learning 84

Machine Learning Data Governance Metadata Data Science 84

DataRobot Blog

SEPTEMBER 13, 2022

The future of business depends on artificial intelligence and machine learning. Many implement machine learning and artificial intelligence to tackle challenges in the age of Big Data. These might include—but are not limited to—deep learning, image recognition and natural language processing.

Forecasting 52

Forecasting Data-driven Machine Learning Optimization 52

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

DataRobot Blog

MAY 26, 2022

Validating Modern Machine Learning (ML) Methods Prior to Productionization. Validating Machine Learning Models. Model validation is a critical component of the model risk management process, in which the proposed model is thoroughly tested to ensure that its design is fit for its objectives. Conclusion.

Risk 52

Risk Modeling Metrics Business Objectives 52

DataRobot Blog

DECEMBER 20, 2022

DataRobot combines these datasets and data types into one training dataset used to build machine learning models. Because our training dataset is multimodal and contains imagery data of residential properties in Madrid, DataRobot used machine learning models that contain deep learning based image featurizers.

Management 59

Management Machine Learning Optimization Modeling 59

BizAcuity

MARCH 31, 2022

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. High frequency trading machines or HFTs use AI for making intraday trading simpler. AI Services.

Data Analytics 52

Data Analytics Analytics Prescriptive Analytics Predictive Analytics 52

IBM Big Data Hub

MAY 17, 2024

Poorly run implementations of traditional or generative AI technology in commerce—such as deploying deep learning models trained on inadequate or inappropriate data—lead to bad experiences that alienate both consumers and businesses.  The applications of AI in commerce are vast and varied.

B2B 64

B2B Interactive Optimization Data-driven 64

Ontotext

FEBRUARY 26, 2024

Risk management : Understanding the correlation between events and stock price fluctuations helps manage risk. Using machine learning, RED indicates the impact of events on stock prices. Investors make informed decisions about buying, holding, or selling stocks by analyzing these events.

Data-driven 59

Data-driven Risk Modeling Risk Management 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

AUGUST 10, 2021

At the center of every machine learning or artificial intelligence application is the ML/AI model that is built with data, algorithms and code. PyTorch: used for deep learning models, like natural language processing and computer vision. It’s used for developing deep learning models.

Modeling 64

Modeling IT Deep Learning Risk Management 64