Add ML intro and business intelligence

src/ainotes.cls

@@ -16,6 +16,8 @@
 \usepackage{scrlayer-scrpage}
 \usepackage{scrhack, algorithm, listings}
 \usepackage{array, makecell}
+\usepackage{acro}
+
 \geometry{ margin=3cm, lmargin=1.5cm, rmargin=4.5cm, marginparwidth=3cm }
 \hypersetup{ colorlinks, citecolor=black, filecolor=black, linkcolor=black, urlcolor=black, linktoc=all }
 

src/machine-learning-and-data-mining/ainotes.cls

@@ -0,0 +1 @@
+../ainotes.cls

src/machine-learning-and-data-mining/main.tex

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+\documentclass[11pt]{ainotes}
+
+\title{Machine Learning and Data Mining}
+\date{2023 -- 2024}
+
+\DeclareAcronym{oltp}{short=OLTP, long=On-Line Transaction Processing}
+\DeclareAcronym{erp}{short=ERP, long=Enterprise Resource Planning}
+\DeclareAcronym{mis}{short=MIS, long=Management Information System}
+\DeclareAcronym{dss}{short=DSS, long=Decision Support System}
+\DeclareAcronym{eis}{short=EIS, long=Executive Information System}
+\DeclareAcronym{olap}{short=OLAP, long=On-Line Analysical Processing}
+\DeclareAcronym{bi}{short=BI, long=Business Intelligence}
+\DeclareAcronym{dwh}{short=DWH, long=Data Warehouse}
+\DeclareAcronym{dm}{short=DM, long=Data Mart}
+
+
+\begin{document}
+
+    \makenotesfront
+    \printacronyms
+    \newpage
+
+    \input{sections/_intro.tex}
+    \input{sections/_bi.tex}
+
+\end{document}

src/machine-learning-and-data-mining/sections/_bi.tex

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+\chapter{Business Intelligence}
+
+
+\begin{description}
+    \item[\Acl{bi}] \marginnote{\Acl{bi}}
+        Transform raw data into information.
+        Deliver the right information to the right people at the right time through the right channel.
+
+    \item[\Ac{dwh}] \marginnote{\Acl{dwh}}
+        Optimized repository that stores information for decision making processes.
+        \Acp{dwh} are a specific type of \ac{dss}.
+
+        Features:
+        \begin{itemize}
+            \item Subject-oriented: focused on enterprise specific concepts.
+            \item Integrates data from different sources and provides an unified view.
+            \item Non-volatile storage with change tracking. 
+        \end{itemize}
+
+    \item[\Ac{dm}] \marginnote{\Acl{dm}}
+        Subset of the primary \ac{dwh} with information relevant to a specific business area.
+\end{description}

src/machine-learning-and-data-mining/sections/_intro.tex

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+\chapter{Introduction}
+
+
+\section{Data}
+
+\begin{description}
+    \item[Data] \marginnote{Data}
+        Collection of raw values.
+
+    \item[Information] \marginnote{Information}
+        Organized data (e.g. relationships, context, \dots).
+
+    \item[Knowledge] \marginnote{Knowledge}
+        Understanding information.
+\end{description}
+
+
+\subsection{Data sources}
+\begin{description}
+    \item[Transaction] \marginnote{Transaction}
+        Business event that generates or modifies data in an information system (e.g. database).
+
+    \item[Signal] \marginnote{Signal}
+        Measure produced by a sensor.
+
+    \item[External subjects]
+\end{description}
+
+
+\subsection{Software}
+\begin{description}
+    \item[\Ac{oltp}] \marginnote{\Acl{oltp}} 
+        Class of programs to support transaction oriented applications and data storage.
+        Suitable for real-time applications.
+
+    \item[\Ac{erp}] \marginnote{\Acl{erp}} 
+        Integrated system to manage all the processes of a business.
+        Uses a shared database for all applications.
+        Suitable for real-time applications.
+\end{description}
+
+
+\subsection{Insight}
+Decision can be classified as:
+\begin{descriptionlist}
+    \item[Structured] \marginnote{Structured decision}
+        Established and well understood situations.
+        What is needed is known.
+    \item[Unstructured] \marginnote{Unstructured decision}
+        Unplanned and unclear situations.
+        What is needed for the decision is unknown.
+\end{descriptionlist}
+
+Different levels of insight can be extracted by:
+\begin{descriptionlist}
+    \item[\Ac{mis}] \marginnote{\Acl{mis}}
+        Standardized reporting system built on existing \ac{oltp}.
+        Used for structured decisions.
+
+    \item[\Ac{dss}] \marginnote{\Acl{dss}}
+        Analytical system to provide support for unstructured decisions.
+
+    \item[\Ac{eis}] \marginnote{\Acl{eis}}
+        Formulate high level decisions that impact the organization.
+
+    \item[\Ac{olap}] \marginnote{\Acl{olap}}
+        Grouped analysis of multidimensional data.
+        Involves large amount of data.
+
+    \item[\Ac{bi}] \marginnote{\Acl{bi}}
+        Applications, infrastructure, tools and best practices to analyze information.
+\end{descriptionlist}
+
+
+
+\begin{description}
+    \item[Big data] \marginnote{Big data}
+        Large and/or complex and/or fast changing collection of data that traditional DBMSs are unable to process.
+        \begin{description}
+            \item[Structured] e.g. relational tables.
+            \item[Unstructured] e.g. videos.
+            \item[Semi-structured] e.g. JSON.   
+        \end{description}
+
+    \item[Anaylitics] \marginnote{Anaylitics}
+        Structured decision driven by data.
+
+    \item[Data mining] \marginnote{Data mining}
+        Discovery process for unstructured decisions.
+        \begin{figure}[ht]
+            \centering
+            \includegraphics[width=0.8\textwidth]{img/data_mining_process.png}
+            \caption{Data mining process}
+        \end{figure}
+
+    \item[Machine learning] \marginnote{Machine learning}
+        Learning models and algorithms that allow to extract patterns from data.
+\end{description}