AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

Large language models are typically refined after pretraining using either supervised fine-tuning (SFT) or reinforcement fine-tuning (RFT), each with distinct strengths and limitations. SFT is ...

Abstract: Direct Current (DC) motors are extensively used in industrial applications for their versatility in speed control and adaptability. This paper introduces a Reinforcement Learning (RL)-based ...

Postpartum depression (PPD) is a common and serious mental health complication after childbirth, with potential negative consequences for both the mother and her infant. This study aimed to develop an ...

In today’s digital background, sentiment analysis has become an essential factor of Natural Language Processing (NLP), offering valuable insights from vast online data sources. This paper presents a ...

Abstract: This work is proposing a new approach for the design of PID controllers by employing a machine learning technique called Random Forest. Conventional design of a PID controller falls into an ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this research work authors have experimentally validated a blend of Machine ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

Critical transitions can model abrupt regime shifts in socio-ecological systems. While generic early warning signals that apply across systems have been investigated, no universal signal exists. We ...