![]() ![]() And there are a lot of things around implementing an AI/ ML project, which include non-technical legal and ethical issues, and technical issues like bias and security.įor more ML/ AI/ Data Science learning materials, please check my previous posts. Being the bratty friend of their little sister never gave me much appeal. After deployment, the model serving, monitoring, and maintenance are also critical steps. by Sylvie Haas ( 226 ) 3.99 I’ve had a crush on my best friend’s older brothers for as long as I can rememberlong before they made a fortune designing high-end homes, and their success puts them even further out of my league. This includes the steps from the very beginning like collecting data, making data ready for learning, engineering features, training model, evaluating, and finally operationalizing. I guess in the future, many citizen data scientists might use out-of-the-box applications or platforms to leverage AI/ ML in their daily work without even having an understanding of how things are done.īut in reality, at this point, a lot of us as data scientists/ professionals, need to go through a very long and complex process to make sure the value of the business will be derived it. ![]()
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