Advancements in Artificial Intelligence: Machine Learning Techniques and Their Real-World Applications

Abstract

Artificial Intelligence (AI) has made major advancements in recent years, with Machine Learning (ML) emerging as one of its most potent subfields. Machine learning techniques, such as supervised learning, unsupervised learning, reinforcement learning, and deep learning, have transformed various sectors by enabling systems to learn from data and make intelligent judgements. the newest breakthroughs in machine learning techniques and their real-world applications across diverse sectors, including healthcare, banking, transportation, and entertainment. We analyse the evolution of algorithms, increases in computer power, and the rising availability of huge data, all of which have contributed to AI's rapid advancement. Additionally, we explore issues such as model interpretability, bias in training data, and ethical implications. By emphasising cutting-edge ML models and their implementations, this article seeks to provide an overview of how machine learning is influencing industries and transforming the way we address challenging challenges.