add some impl stuff

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lukas-heiligenbrunner 2024-04-26 07:07:44 +02:00
parent fa73e4e4ea
commit 0fc6898c70
3 changed files with 20 additions and 0 deletions

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\section{Implementation}\label{sec:implementation} \section{Implementation}\label{sec:implementation}
\subsection{Dagster with Label-Studio}
The main goal is to implement an active learning loop with the help of Dagster and Label-Studio.
The task was split as much as possible...
\subsection{Jupyter}
To get accurate performance measures the active-learning process was implemented in a Jupyter notebook first.
This helps to choose which of the methods performs the best and which one to use in the final Dagster pipeline.
A straight forward machine-learning pipeline was implemented with the help of Pytorch and RESNet.
\begin{lstlisting}
# todo listing of the sample selection process
\end{lstlisting}

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\usepackage{amsmath} \usepackage{amsmath}
\usepackage{mathtools} \usepackage{mathtools}
\usepackage{hyperref} \usepackage{hyperref}
\usepackage{listings}
\usepackage[inline]{enumitem} \usepackage[inline]{enumitem}

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\subsection{Material}\label{subsec:material} \subsection{Material}\label{subsec:material}
\subsubsection{Dagster} \subsubsection{Dagster}
Dagster is a data orchestrator for machine learning, analytics, and ETL workflows.
It lets you define pipelines in terms of the data flow between reusable, logical components.
Dagster is a tool that helps to build scalable and reliable data workflows.
\subsubsection{Label-Studio} \subsubsection{Label-Studio}
\subsubsection{Pytorch} \subsubsection{Pytorch}
\subsubsection{NVTec} \subsubsection{NVTec}