Advancements in Machine Learning: Techniques, Applications, and Challenges

EasyChair Preprint 15664

Abstract

Machine learning (ML) has emerged as one of the most transformative technologies in recent
years, driving innovation across various fields such as healthcare, finance, transportation, and
beyond. This paper explores key advancements in machine learning, focusing on different
techniques such as supervised learning, unsupervised learning, and reinforcement learning.
Additionally, it highlights recent applications in real-world scenarios and discusses the
challenges faced by researchers and practitioners in implementing ML models. Through a
comprehensive evaluation of the existing literature and experiments, this paper offers insights
into future directions for ML research, particularly in the context of increasing data volumes
and computational complexities.

Keyphrases: Applications, Challenges, Reinforcement Learning, machine learning, supervised learning, unsupervised learning

@booklet{EasyChair:15664,
  author    = {Ryu Nao and Takumi Miyo and Chi Zhang},
  title     = {Advancements in Machine Learning: Techniques, Applications, and Challenges},
  howpublished = {EasyChair Preprint 15664},
  year      = {EasyChair, 2025}}