by Angela Guess
Nikhil Dandekar recently answered the question, “How can one become a good machine learning engineer?” on Quora. Dandekar responded, “Here is a list of must-have traits, in no particular order: (1) You need to enjoy an iterative process of development. If you want to build a machine learning system, you need to be able to build a version 0.1 using a very simple model quickly. Then iterate on getting it better at every successive stage. (2) You also need to have a good intuition for when to stop. In any machine learning system, you can always improve the accuracy by iterating on it more. But at some point, the effort you put into it exceeds the value you derive from it. You need to be able to identify that point.”
He goes on, “(3) You should be comfortable with failure. A lot of your models and experiments will fail. And that’s ok. (4) You should be driven by curiosity. The best people are the ones who are genuinely curious about the world around them and channel that curiosity when working on machine learning. (5) You need to have a good data intuition. You should be good at identifying patterns in the data. Being able to create quick data visualizations (using R, Python, Matlab or Excel etc.) helps. (6) You need to have a good sense of metrics and be metrics-driven. You should to be able to establish metrics that define success or failure of your system. You should feel comfortable with blind experiments [1] and terms like precision, recall, accuracy, ROC, conversion rates, NDCG etc.”
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