While cloud computing has provided major benefits by maximizing the use of resources within a cloud, the current solutions still face many challenges. In this paper, we propose performance enhancements for cloud computations, provided by integrating hardware acceleration into the computation services. We extend the Hadoop framework by adding provisions for hardware acceleration using Field Programmable Gate Arrays (FPGAs). Hardware acceleration using energy efficient FPGAs is used as a service within the clouds or to offload computations when needed. It can provide additional sources of revenues, reduced operating costs, and increased resource utilization. We developed a custom Hadoop system and tested four applications commonly used for machine learning and deep learning. The results show the benefits of hardware acceleration and the high performance gains in smaller execution times and energy consumption.