Running a training algorithm is such a time-consuming task when you are building a machine learning application. If you are developing it with your computer, you cannot do anything else for a long period of time (hours and maybe days) on that machine. Especially when we do parallel processing using …

Once you create an awesome data science application, it is time for you to deploy it. There are many ways to productionise them. The focus here is deploying Spark applications by using the AWS big data infrastructure. From my experience with the AWS stack and Spark development, I will discuss …