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<!DOCTYPE html>
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<meta name="author" content="HAS Sothea, PhD">
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<title>Exploratory Data Analysis & Unsupervised Learning </title>
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<h1 class="title"><strong>Exploratory Data Analysis & Unsupervised Learning</strong> <img src="./img/AMS_logo.png#right" class="img-fluid" style="width:0.625in"> <img src="./img/itc.png#left" class="img-fluid" style="position: relative; bottom: 5px;width:0.41667in"></h1>
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<div class="quarto-title-meta-container">
<div class="quarto-title-meta-column-start">
<div class="quarto-title-meta">
<div>
<div class="quarto-title-meta-heading">Author</div>
<div class="quarto-title-meta-contents">
<p><a href="https://hassothea.github.io/">HAS Sothea, PhD</a> </p>
</div>
</div>
<div>
<div class="quarto-title-meta-heading">Published</div>
<div class="quarto-title-meta-contents">
<p class="date">October 30, 2024</p>
</div>
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<div id="quarto-margin-sidebar" class="sidebar margin-sidebar">
<nav id="TOC" role="doc-toc" class="toc-active">
<h2 id="toc-title">Table of contents</h2>
<ul>
<li><a href="#introduction" id="toc-introduction" class="nav-link active" data-scroll-target="#introduction">Introduction</a></li>
<li><a href="#course-criteria" id="toc-course-criteria" class="nav-link" data-scroll-target="#course-criteria">Course Criteria</a>
<ul class="collapse">
<li><a href="#programming" id="toc-programming" class="nav-link" data-scroll-target="#programming">Programming:</a></li>
</ul></li>
<li><a href="#tp-sections" id="toc-tp-sections" class="nav-link" data-scroll-target="#tp-sections">TP Sections</a></li>
<li><a href="#midterms-exams-and-projects" id="toc-midterms-exams-and-projects" class="nav-link" data-scroll-target="#midterms-exams-and-projects">Midterms, Exams and Projects</a>
<ul class="collapse">
<li><a href="#project" id="toc-project" class="nav-link" data-scroll-target="#project">✏️ Project:</a></li>
</ul></li>
<li><a href="#resources-and-further-reading" id="toc-resources-and-further-reading" class="nav-link" data-scroll-target="#resources-and-further-reading">Resources and Further Reading</a></li>
</ul>
</nav>
</div>
<main class="content quarto-banner-title-block" id="quarto-document-content">
<section id="introduction" class="level1">
<h1>Introduction</h1>
<p>Welcome to the practical session webpage on <strong>Exploratory Data Analysis (EDA) and Unsupervised Learning</strong>! This session is designed to equip you with the essential skills and techniques to explore and understand your data before diving into more complex modeling tasks. By the end of this session, you will be adept at uncovering crucial insights hidden within the data and leveraging this knowledge to guide your analysis effectively. You will approach data analysis with a clear objective, applying a variety of techniques to understand, interpret, and make informed decisions based on the data. Additionally, you will be able to present your findings visually, making them accessible for both technical and general audiences.</p>
<hr>
</section>
<section id="course-criteria" class="level1">
<h1>Course Criteria</h1>
<table class="caption-top table">
<thead>
<tr class="header">
<th style="text-align: left;"><strong><code>Criteria</code></strong></th>
<th style="text-align: center;"><strong><code>Percentage</code></strong></th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td style="text-align: left;">Attendance</td>
<td style="text-align: center;">10%</td>
</tr>
<tr class="even">
<td style="text-align: left;">Participation & quiz</td>
<td style="text-align: center;">10%</td>
</tr>
<tr class="odd">
<td style="text-align: left;">Midterm Exam or/and Project</td>
<td style="text-align: center;">15%+15%</td>
</tr>
<tr class="even">
<td style="text-align: left;">Final Exam</td>
<td style="text-align: center;">20%</td>
</tr>
<tr class="odd">
<td style="text-align: left;">Final Project & Presentation</td>
<td style="text-align: center;">30%</td>
</tr>
</tbody>
</table>
<section id="programming" class="level2">
<h2 class="anchored" data-anchor-id="programming">Programming:</h2>
<blockquote class="blockquote">
<p>You are free you use your favorite programming language <a href="https://www.python.org/" target="_blank"><img src="./img/python.png" class="img-fluid" style="position: relative; bottom: 0px" width="30"></a> <code>Python</code> or <a href="https://www.r-project.org/" target="_blank"><img src="./img/R_logo.png" class="img-fluid" style="position: relative; bottom: 0px" width="30"></a>…</p>
</blockquote>
<div class="tabset-margin-container"></div><div class="panel-tabset">
<ul class="nav nav-tabs" role="tablist"><li class="nav-item" role="presentation"><a class="nav-link active" id="tabset-1-1-tab" data-bs-toggle="tab" data-bs-target="#tabset-1-1" role="tab" aria-controls="tabset-1-1" aria-selected="true" href=""><code>Python</code></a></li><li class="nav-item" role="presentation"><a class="nav-link" id="tabset-1-2-tab" data-bs-toggle="tab" data-bs-target="#tabset-1-2" role="tab" aria-controls="tabset-1-2" aria-selected="false" href=""><code>R</code></a></li></ul>
<div class="tab-content">
<div id="tabset-1-1" class="tab-pane active" role="tabpanel" aria-labelledby="tabset-1-1-tab">
<ul>
<li><a href="https://docs.jupyter.org/en/latest/" target="_blank"><img src="./img/jupyter.png" class="img-fluid" style="position: relative; bottom: 0px" width="30"> Jupyter Notebook</a></li>
<li><a href="https://colab.research.google.com/" target="_blank"><img src="./img/colab.png" class="img-fluid" style="position: relative; bottom: 0px" width="30"> Google colab</a></li>
<li><a href="https://matplotlib.org/" target="_blank"><img src="./img/plt_logo.png" class="img-fluid" style="position: relative; bottom: 0px" width="35"> Matplotlib</a></li>
<li><a href="https://seaborn.pydata.org/" target="_blank"><img src="./img/sns_logo.svg" class="img-fluid" style="position: relative; bottom: 0px" width="30"> Seaborn</a></li>
</ul>
</div>
<div id="tabset-1-2" class="tab-pane" role="tabpanel" aria-labelledby="tabset-1-2-tab">
<ul>
<li><a href="https://quarto.org/" target="_blank"><img src="./img/quarto_logo.png" class="img-fluid" style="position: relative; bottom: 0px" width="60"> Rmarkdown/Quarto</a></li>
<li><a href="https://ggplot2.tidyverse.org/" target="_blank"><img src="./img/posit_logo.png" class="img-fluid" style="position: relative; bottom: 0px" width="25"> Posit cloud</a></li>
<li><a href="https://ggplot2.tidyverse.org/" target="_blank"><img src="./img/ggplot_logo.png" class="img-fluid" style="position: relative; bottom: 0px" width="27"> Ggplot2</a></li>
<li><a href="https://www.tidyverse.org/" target="_blank"><img src="./img/tidyverse_logo.png" class="img-fluid" style="position: relative; bottom: 0px" width="30"> Tidyverse</a></li>
</ul>
</div>
</div>
</div>
<hr>
</section>
</section>
<section id="tp-sections" class="level1">
<h1>TP Sections</h1>
<div class="line-block"><strong>Note</strong>: The following table of contents will be progressively updated according to the course advancement.</div>
<table class="caption-top table">
<thead>
<tr class="header">
<th style="text-align: left;">Topic</th>
<th style="text-align: center;">TP</th>
<th style="text-align: center;">Solution</th>
<th style="text-align: center;">Remark</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td style="text-align: left;">Univariate Analysis</td>
<td style="text-align: center;"><a href="https://hassothea.github.io/EDA_ITC/TPs/TP1_Variable_Types_Descriptive_Statistics.html" target="_blank">TP1-Gapminder</a></td>
<td style="text-align: center;"><a href="https://hassothea.github.io/EDA_ITC/Solutions/TP1_Variable_Types_Descriptive_Statistics_sol.html" target="_blank">TP1-solution</a></td>
<td style="text-align: center;">✅ Completed</td>
</tr>
<tr class="even">
<td style="text-align: left;">Bivariate Analysis</td>
<td style="text-align: center;"><a href="https://hassothea.github.io/EDA_ITC/TPs/TP2_Bivariate_Analysis.html" target="_blank">TP2-Bivariate-Gapminder</a></td>
<td style="text-align: center;"><a href="https://hassothea.github.io/EDA_ITC/Solutions/TP2_Bivariate_Analysis_sol.html" target="_blank">TP2-solution</a></td>
<td style="text-align: center;">✅ Completed</td>
</tr>
<tr class="odd">
<td style="text-align: left;">Data Preprocessing</td>
<td style="text-align: center;"><a href="https://hassothea.github.io/EDA_ITC/TPs/TP3_Data_Preprocessing.html" target="_blank">TP3-Preprocessing</a></td>
<td style="text-align: center;"><a href="https://hassothea.github.io/EDA_ITC/Solutions/TP3_Data_Preprocessing_sol.html" target="_blank">TP3-solution</a></td>
<td style="text-align: center;">✅ Completed</td>
</tr>
<tr class="even">
<td style="text-align: left;">Clustering</td>
<td style="text-align: center;"><a href="https://hassothea.github.io/EDA_ITC/TPs/TP4_Clustering.html" target="_blank">TP4-Clustering</a></td>
<td style="text-align: center;"><a href="https://hassothea.github.io/EDA_ITC/Solutions/TP4_Clustering_sol.html" target="_blank">TP4-solution</a></td>
<td style="text-align: center;">✅ Completed</td>
</tr>
<tr class="odd">
<td style="text-align: left;">Gaussian Mixture Models & EM Algorithm</td>
<td style="text-align: center;"><a href="https://hassothea.github.io/EDA_ITC/TPs/TP5_GMM_EM.html" target="_blank">TP5-GMM_EM</a></td>
<td style="text-align: center;"><a href="https://hassothea.github.io/EDA_ITC/Solutions/TP5_GMM_EM_sol.html" target="_blank">TP5-solution</a></td>
<td style="text-align: center;">✅ Completed</td>
</tr>
<tr class="even">
<td style="text-align: left;">Principal Component Analysis (PCA)</td>
<td style="text-align: center;"><a href="https://hassothea.github.io/EDA_ITC/TPs/TP6_PCA.html" target="_blank">TP6-PCA</a></td>
<td style="text-align: center;">TP6-Solution</td> <!-- <a href="https://hassothea.github.io/EDA_ITC/Solutions/TP5_GMM_EM_sol.html" target="_blank">TP5-solution</a> -->
<td style="text-align: center;"><code>...Loading</code></td>
</tr>
</tbody>
</table>
<!--](https://hassothea.github.io/EDA_ITC/TPs/TP3_Data_Preprocessing.html){target="_blank"} | [TP3-solution](https://hassothea.github.io/EDA_ITC/Solutions/TP3_Data_Preprocessing_sol.html){target="_blank"} | ✅ Completed | -->
</section>
<section id="midterms-exams-and-projects" class="level1">
<h1>Midterms, Exams and Projects</h1>
<p>In this section, you will find all the information related to the midterms, exams and projects including instructions, starting dates and the deadlines.</p>
<section id="project" class="level2">
<h2 class="anchored" data-anchor-id="project">✏️ Project:</h2>
<ul>
<li>Deadline for the report: <code>...Loading</code>.</li>
<li>Where to submit: <code>...Loading</code></li>
<li>Your report should be in (your favorite) <strong>PDF</strong> format and include the following criteria:
<ul>
<li><strong>Members’ names & contributions</strong>.
<ul>
<li>Clearly state each member’s contribution to the report.</li>
<li>For example:
<ul>
<li><strong>Luffy</strong>: Introduction, Data Preprocessing</li>
<li><strong>Gojo</strong>: Exploratory Data Analysis, Model Development</li>
<li><strong>Naruto</strong>: Results and Evaluation, Conclusion</li>
</ul></li>
</ul></li>
<li><strong>Introduction</strong>:
<ul>
<li>Clearly state the objectives and purpose of the analysis.</li>
<li>Provide a brief descriptive statistics of the dataset.</li>
</ul></li>
<li><strong>Data Preprocessing</strong>:
<ul>
<li>Detail steps taken to clean and preprocess the data.</li>
<li>Explain handling of missing values and outliers.</li>
<li>Describe any feature engineering techniques applied.</li>
</ul></li>
<li><strong>Exploratory Data Analysis (EDA)</strong>:
<ul>
<li>Include visualizations (charts, graphs) and descriptive statistics.</li>
<li>Identify key patterns, trends, and anomalies in the data.</li>
</ul></li>
<li><strong>Unsupervised/supervised Tasks</strong>:
<ul>
<li>Exploring structures or connections of the data according the flow of your analysis.</li>
<li>Provide details on clustering methods or model training, validation, and testing processes.</li>
<li>Include any choice of parameters of unsupervised tasks or hyperparameter tuning and model optimizations.</li>
</ul></li>
<li><strong>Results and Evaluation</strong>:
<ul>
<li>Present the resulting performance (e.g., obtained structures or accuracy, precision, recall, F1-score, RMSE).</li>
<li>Compare performance across different methods if multiple were used.</li>
<li>Highlight any insights or conclusions drawn from the implemented methods/models.</li>
</ul></li>
<li><strong>Conclusion</strong>:
<ul>
<li>Summarize key findings and their implications.</li>
<li>Discuss any limitations of the analysis.</li>
<li>Suggest potential areas for future research or improvement.</li>
</ul></li>
<li><strong>References</strong>:
<ul>
<li>Cite all sources of data and any external libraries or tools used.</li>
<li>Include academic references for any theoretical concepts or methods applied.</li>
</ul></li>
<li><strong>Appendix (Optional)</strong>:
<ul>
<li>Provide additional figures, tables, or code snippets that support the analysis.</li>
</ul></li>
</ul></li>
<li><strong>Presentation</strong>:
<ul>
<li>A possible dates: <code>...Loading</code>.</li>
</ul></li>
</ul>
<hr>
</section>
</section>
<section id="resources-and-further-reading" class="level1">
<h1>Resources and Further Reading</h1>
<p>Here, you will find additional resources, including books, research papers, and online courses, to further your understanding of <strong>Exploratory Data Analysis and Unsupervised Learning</strong>.</p>
<p>📚 You will find these books/links helpful…</p>
<ul>
<li><p><a href="https://github.com/PacktPublishing/Exploratory-Data-Analysis-with-Python-Cookbook?tab=readme-ov-file" target="_blank">Exploratory-Data-Analysis-with-Python-Cookbook</a></p></li>
<li><p><a href="https://haralick.org/DV/Handbook_of_Data_Visualization.pdf" target="_blank">Handbook of Data Visualization, Chen et al.</a></p></li>
<li><p><a href="https://wesmckinney.com/book/" target="_blank">Python for Data Analysis, Wes M.</a></p></li>
<li><p><a href="https://bookdown.org/rdpeng/exdata/" target="_blank">Exploratory Data Analysis with R, Roger D. Peng</a></p></li>
<li><p><a href="https://batrachos.com/sites/default/files/pictures/Books/Wickham_Grolemund_2017_R%20for%20Data%20Science.pdf" target="_blank">R for Data Science, Hadley W. and Garrett G.</a></p></li>
</ul>
<hr>
</section>
</main>
<!-- /main column -->
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