Summary
In this chapter, we discussed how to build quick visualizations for analytics and machine learning use cases using Amazon SageMaker Data Wrangler. We showed a few of the various exploratory data analysis, plotting, and data transformation options available within SageMaker Data Wrangler. The ability to quickly and easily build these visualizations and bias and quality reports is very important for data scientists and practitioners in the machine learning domain since it helps in cutting down on the cost and effort associated with exploratory data analysis significantly. In addition, we discussed Amazon’s graphics-optimized instances that are available for high-performance computing applications such as game streaming, rendering, and machine learning use cases.
From the next chapter onwards, we will start discussing various applications of high-performance computing and applied machine learning, with the first one being computational fluid dynamics.
