This article discusses the use of latent variable models in machine learning, specifically in combination with neural networks and back propagation. It includes four…
Browsing: Clustering
This article discusses the importance of interpretability in machine learning, particularly in high-stakes applications such as healthcare. The authors propose a new method that…
Data science is one of the most rewarding and in-demand fields in the 21st century. Data scientists are responsible for collecting, cleaning, analyzing, and…
Information theory is a mathematical infrastructure to deal with manipulation of information and has a significant influence on the design of efficient and reliable…
Machine learning is a subset of artificial intelligence that enables systems to learn and improve from experience autonomously. This article provides an overview of…
Predictive analytics is an analytics process that uses statistics and modeling techniques to make informed decisions and predictions about future outcomes based on current…
Machine learning is an increasingly important tool in microbiology, used for tasks such as predicting antibiotic resistance and associating human microbiome features with complex…
This article discusses a new approach for manatee counting using Anisographic Gaussian Kernel (AGK) based crowd counting. The proposed method employs line-segment annotation, using…
This article explores 10 free datasets for machine learning projects, including the Iris dataset, MNIST dataset, CIFAR-10 and CIFAR-100 datasets, and the UCI Machine…
Predictive analytics is a powerful tool for uncovering hidden patterns and relationships within data, enabling the prediction of future outcomes. This article provides an…