Machine learning and artificial intelligence are effective in addressing complicated problems including energy optimization, workflow scheduling, video gaming, and cloud computing. When machine learning and cloud computing methods are coupled, they help obtain better results by improving the performance of cloud data centers compared to current solutions used by various academics. It is also useful for relocating virtual machines based on current traffic conditions, including fluctuations caused by network congestion and bandwidth availability. The survey intends to provide improvements in dynamic load allocation, work scheduling, energy optimization, live migration, mobile cloud computing, and cloud security through machine learning categorization. Machine learning algorithms automate pattern recognition and simplify the learning process. The paper includes an introduction, motivation, background study, cloud-machine learning integration framework, best practices for introducing machine learning in cloud computing, and the work's purpose. The paper discusses machine learning-based cloud services and the use of artificial intelligence in various cloud computing platforms.
Cloud computing, Resource allocation, Data center, chatbot, Internet of Things.