The convergence of Machine Learning (ML) and Artificial Intelligence (AI) with the Internet of Things (IoT) has unleashed a paradigm shift in the capabilities of interconnected devices. This paper explores the integration techniques and diverse applications of ML and AI in the IoT ecosystem. The synergy between these technologies empowers IoT systems to process vast amounts of data, make intelligent decisions, and enhance overall efficiency. The integration techniques encompassed in this study include data preprocessing, feature engineering, and model optimization tailored for IoT environments. Furthermore, the paper delves into the challenges and solutions associated with deploying ML and AI algorithms on resource-constrained IoT devices. In terms of applications, the research covers a broad spectrum, including predictive maintenance, anomaly detection, smart healthcare, industrial automation, and energy management. Case studies and real-world examples illustrate how ML and AI bring about transformative changes in these domains, paving the way for more sustainable and intelligent IoT solutions.