Many companies are utilizing the cloud for their day to day activities. Many big cloud service providers like AWS, Microsoft Azure have been successfully serving its increasing customer base. A brief understanding of the characteristics of production virtual machine (VM) workloads of large cloud providers can inform the provider's resource management systems. In our project, we will be analyzing Microsoft Azure’s VM CPU utilization dataset released in 2017. We predict the VM workload from the CPU usage pattern like minimum, maximum, and average from the Azure dataset. Different techniques among Deep learning are used for the prediction by considering the history of the workload. By considering real VM traces, we can show that the prediction-informed schedules increase utilization and stop physical resource exhaustion. We can arrive at the conclusion that cloud service providers can use their workloads’ characteristics and machine learning techniques to enhance resource management greatly.