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Andras Schmelczer 2022-08-14 20:36:06 +02:00
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docs/thesis/chapters/appendix.tex
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\chapter{Best practices assessment} \label{appendix:practices}
Similar to the approach of \cite{serban2020adoption}, participants are asked about their team's level of AI/ML deployment best practices adoption. The questions come from the entries of Tables \ref{table:best-practices-1} and \ref{table:best-practices-2} where \textit{GreatAI} was determined to provide a support level of \textit{Fully automated}.
Similarly to the approach of \cite{serban2020adoption}, participants are asked about their team's level of adoption of AI/ML deployment best practices. The questions come from the entries of Tables \ref{table:best-practices-1} and \ref{table:best-practices-2} where \textit{GreatAI} was determined to provide a support level of \textit{Fully automated}.
\textbf{How well did the previous AI deployment that you have collaborated on implemented the following best-practices?} \textit{Each statement can be rated on a 5-point Likert scale or as ``Not applicable''.}
\textbf{How well did the previous AI deployment that you collaborated on implement the following best practices?} \textit{Each statement can be rated on a 5-point Likert scale or as ``Not applicable''.}
\begin{enumerate}
\item Write reusable scripts for data cleaning and merging
\item Make data sets available on shared infrastructure
\item Make datasets available on shared infrastructure
\item Use versioning for data, model, configurations and training scripts
\item Continuously monitor the behaviour of deployed models
\item Log production predictions with the model's version and input data
\item Store models in a single format for ease of use
\item Equip with web interface, package image, provide REST API
\item Equip with a web interface, package image, provide REST API
\item Provide simple API for serving batch and real-time requests
\item Integration with existing data infrastructure
\item Querying, visualising and understanding metrics and event logging