Tag: Deep neural networks
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Stacked Ensemble Machine Learning for Predicting Porosity and Absolute Permeability of Carbonate Rock Plugs
Learn how machine learning algorithms can predict porosity and permeability of carbonate rock samples accurately for exploration and groundwater management.
Creating a Nurse Turnover Prediction Model in South Korea Using Machine Learning
This article discusses a nurse turnover prediction model developed by Prof. Hang-Bae Cho from the Seoul National University Biomedical Research Institute. The model uses machine learning techniques to generate accurate predictions, allowing healthcare administrators to better anticipate nursing staff changes. Reuse of any part of the published articles is freely permitted under open access Creative Commons CC BY license.
Generative AI in HR Tech: Streamlining Processes with ChatGPT and Bard
Discover how generative AI and ChatGPT are transforming the HR tech industry. From improved efficiency to job descriptions creation, ChatGPT and other AI-based technologies are revolutionizing HR processes. Companies must keep in mind potential issues such as bias and accuracy, to reap the full benefits.
OpenAI’s Dall-E for 3D Objects: A Preview of Shap-E Tool
OpenAI has developed a new generative model called Shap-E, allowing users to generate 3D assets and neural radiance fields from text and images. Shap-E is compatible only with Nvidia GPUs, requiring high performance CPUs for efficient rendering. Despite the challenging installation process, Shap-E is freely available to use on Microsoft Paint 3D and convert into an STL file for 3D printing.