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Titlebook: Emerging Challenges in Intelligent Management Information Systems; Proceedings of 26th Marcin Hernes,Jaros?aw W?tróbski Conference proceed

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發(fā)表于 2025-3-28 17:25:44 | 只看該作者
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發(fā)表于 2025-3-29 00:00:56 | 只看該作者
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發(fā)表于 2025-3-29 05:22:02 | 只看該作者
Exploring Cause-and-Effect Relationships Between Public Company Press Releases and?Their Stock Priceices on NASDAQ stock exchange, followed by a brief discussion. For this purpose, it was necessary to download the stock quotes of selected companies from the NASDAQ market from public web sources. Additionally, media messages related to selected companies had to be downloaded, and then a news sentim
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發(fā)表于 2025-3-29 09:28:38 | 只看該作者
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發(fā)表于 2025-3-29 12:10:34 | 只看該作者
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發(fā)表于 2025-3-29 15:50:27 | 只看該作者
Forecasting Fuel Retail Sales Volume Using Machine Learning for Sustainable Decision-Makinglume influences the planning of the effective distribution of fuels. Therefore, it impacts all other supply chains and each country‘s economy. .: This research uses machine learning to forecast fuel retail sales volume. The choice of this method and the research subject are based on the complexity o
48#
發(fā)表于 2025-3-29 23:08:14 | 只看該作者
The Effectiveness of?AI Methods Compared to?Statistical Analysis and?Data Modeling in?the?Constructimic AI analysis (AMC) in scoring models for calculating LGD (Losses Given Default) – the bank’s percentage share of credit losses (in case of non-payment or delayed repayment of the loan). Analysis based on simulation data generated on the basis of probability distributions, which were obtained from
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發(fā)表于 2025-3-30 02:44:50 | 只看該作者
Supporting Algorithmic Trading with?Machine Learning: Progress in?Backend Technologyly because of the speed and frequency but also by ruling out the influence of human emotions. Over the years many programming languages were used for machine learning research and system development. Python being easy to learn but still powerful has become popular within the scientific computing com
50#
發(fā)表于 2025-3-30 05:42:50 | 只看該作者
Forecasting e-learning Course Purchases Using Deep Learning Based on Customer Retentiones are based on analyzing many user profile characteristics, which are only sometimes available to e-learning course providers. The aim of this research is to develop a method for forecasting e-learning course purchases using deep learning based on customer retention. The multi-layer perceptron and
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