Machine learning applications have also been extensively ... Qiu et al. 64 used an SVM classifier to predict, using data such as protein sequences and cellular localization, whether a given ...

In contrast, drug repurposing seeks to identify new therapeutic applications ... machine learning techniques, including Logistic Regression, Random Forest, Support Vector Machines (SVM), K-Nearest ...

and exciting ways to apply powerful machine learning tools such as neural networks to existing problems in many different industries. Below is a list of 10 of the most interesting applications.

Machine learning (ML) models have been increasingly ... making trees based on several binary decisions for the inputs. SVM models provide lines or multidimensional hyperplanes for tumor features ...

More information: Yun-Fei Shi et al, Machine Learning for Chemistry: Basics and Applications, Engineering (2023). DOI: 10.1016/j.eng.2023.04.013 Provided by Engineering ...

The Machine Learning: Practical Applications online certificate course from the London School of Economics and Political Science (LSE) focuses on the practical applications of machine learning in ...