Like with movies, I don’t have one favorite machine learning (ML) algorithm, but a few favorites, each for its own reason. Here are some of my top few algorithms and models: Most elegant: The ...

However the dynamic variation in the TST transmit power challenges the served users to develop optimal computing task processing decisions. In this paper we propose an efficient pruning-split long ...

A clustering method suitable for the Bi-LSTM (bidirectional long short-term memory) model for processing power state samples, which can improve learning performance, was studied. The case studies ...

This paper offers a dependable short-term, hourly-ahead forecasting method of PV power generation for the delivery and storage mostly for the grid optimization. A long short-term memory (LSTM)- based ...

Machine learning is a branch of artificial intelligence that includes methods, or algorithms, for automatically creating models from data. Unlike a system that performs a task by following ...

Specialization: Machine LearningInstructor: Geena Kim, Assistant Teaching ProfessorPrior knowledge needed: Calculus, Linear algebra, PythonLearning Outcomes Explain what unsupervised learning is, and ...

Machine learning and deep learning methods. In this study, we used 10 algorithms, both machine learning and deep learning, to establish a corresponding model through the training group, and then ...

SVM is a machine-learning set of algorithms that can be used to predict the occurrence of a particular event by analyzing a set of data and identifying patterns and relationships. Using SVM algorithms ...