Python fosters and accelerates innovation in daily modeling tasks

Mel Meng, Elefante Dominador and Lou Lambe


Academic modeling research has closely followed the most recent technology trend in improving model accuracy, performance, and reliability. However, due to the high degree of specialized skills required to carry out such processes, the engineering community confronts a considerable barrier in reaping the benefits of the majority of the findings. With the fast rise of big data, cloud computing, and AI over the last decade, many of these powerful research tools have become part of the IT infrastructure for a significant portion of the Internet. As a result, using publicly available online resources, anyone with ordinary technical experience may become proficient with these tools in a matter of months. 

For the first time, front-line engineers can play a vital role in innovation with an equitable playing field, bringing decades of specialized research to fruition. In this session, the authors will discuss with the audience a few earlier attempts to incorporate innovation into our daily job using Python. 

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