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mdenolle committed Dec 13, 2024
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148 changes: 110 additions & 38 deletions Chapter1-GettingStarted/1.20_MLGEO_Final_Project.html
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Expand Up @@ -656,9 +656,9 @@ <h1 class="site-logo" id="site-title">ML Geo Curriculum</h1>
</a>
</li>
<li class="toc-h1 nav-item toc-entry">
<a class="reference internal nav-link" href="#presentation-10-minutes-25">
<a class="reference internal nav-link" href="#presentation-10-15-minutes-25">
<strong>
3. Presentation (10 Minutes) - 25%
3. Presentation (10-15 Minutes) - 25%
</strong>
</a>
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Expand Down Expand Up @@ -715,9 +715,9 @@ <h2> Contents </h2>
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<li class="toc-h1 nav-item toc-entry">
<a class="reference internal nav-link" href="#presentation-10-minutes-25">
<a class="reference internal nav-link" href="#presentation-10-15-minutes-25">
<strong>
3. Presentation (10 Minutes) - 25%
3. Presentation (10-15 Minutes) - 25%
</strong>
</a>
</li>
Expand Down Expand Up @@ -753,29 +753,44 @@ <h1>Final Integrated Project in Machine Learning in Geoscience<a class="headerli
<section id="report-5-pages-40">
<h1><strong>1. Report (5 Pages) - 40%</strong><a class="headerlink" href="#report-5-pages-40" title="Permalink to this headline">#</a></h1>
<ul class="simple">
<li><p><strong>Integration and Cohesion (10%)</strong></p>
<li><p><strong>Content &amp; Research Quality (25%)</strong> Quality, depth, and relevance of the research</p>
<ul>
<li><p>Clearly integrates AI-ready data preparation, CML, and DL components into a single narrative.</p></li>
<li><p>Demonstrates the logical progression of methods and their relevance to the geoscientific problem.</p></li>
<li><p>Present a clear statement of an outstanding research question and place it in the context of an up-to-date literature review</p></li>
<li><p>Demonstrates the originality of the research</p></li>
<li><p>Present an AI-ready data set, preliminary analysis with correlation or description of basic data feature, and discuss potential data imbalance within the context of the stated problem.</p></li>
<li><p>Demonstrate strong understanding of classic machine learning and/or deep learning with an example</p></li>
<li><p>Discuss the performance evaluation in the context of training the model and for generalization beyond the data and domain presented in the report.</p></li>
<li><p>Discuss the computational time for training and deploying</p></li>
<li><p>Discuss the appropriateness of computational resources needed</p></li>
</ul>
</li>
<li><p><strong>Scientific Discussion and Interpretation (15%)</strong></p>
<li><p><strong>Structure and Organization (15%)</strong> Coherence, clarity, and flow of the report</p>
<ul>
<li><p>Provides insightful analysis of results, including comparisons between CML and DL methods.</p></li>
<li><p>Discusses trade-offs, advantages, and limitations of the approaches used.</p></li>
<li><p>Includes domain-specific interpretations and implications of findings.</p></li>
<li><p>Logical structure (introduction, body, conclusions, references)</p></li>
<li><p>Well-organized paragraphs with transitions between ideas</p></li>
<li><p>Key points and arguments are clearly presented and easy to follow</p></li>
<li><p>Figures presented have captions and clear labels and are references in the text.</p></li>
</ul>
</li>
<li><p><strong>Clarity and Organization (10%)</strong></p>
<li><p><strong>Clarity and Writing Style (20%)</strong> Quality &amp; Effectiveness in Writing</p>
<ul>
<li><p>The report is well-structured, concise, and within the 5-page limit (excluding references and appendices).</p></li>
<li><p>Includes high-quality figures, tables, and diagrams to support the narrative.</p></li>
<li><p>Clear concise language</p></li>
<li><p>Minimal grammar or spelling errors</p></li>
<li><p>Professional and academic tone appropriate for the field</p></li>
</ul>
</li>
<li><p><strong>Team Contributions (5%)</strong></p>
<li><p><strong>Critical Thinking &amp; Analysis (20%)</strong> Depth of analysis and reflection on the research topic</p>
<ul>
<li><p>The GitHub demonstrates that every team member has contributed to the github repository</p></li>
<li><p>The presentations had time allocated for each group members, each were assigned with a specific task to present.</p></li>
<li><p>The analysis goes beyond simple description and shows depths of thought</p></li>
<li><p>Acknowledges alternative perspectives or potential limitations in the research</p></li>
<li><p>Demonstrates original thinking and critical engagement with the research</p></li>
</ul>
</li>
<li><p><strong>Formatting &amp; Citations (10%)</strong> Adherence to format guidelines and proper citation of sources</p>
<ul>
<li><p>Follows formatting requirements (e.g., margins, font, length)</p></li>
<li><p>Correct use of citation style (e.g., APA, MLA, Chicago)</p></li>
<li><p>Correctly state the author’s CredIT (every student enrolled needs to be associated with a contribution and the CreDIT statement will assert that)</p></li>
</ul>
</li>
</ul>
Expand All @@ -784,49 +799,106 @@ <h1><strong>1. Report (5 Pages) - 40%</strong><a class="headerlink" href="#repor
<section id="github-repository-35">
<h1><strong>2. GitHub Repository - 35%</strong><a class="headerlink" href="#github-repository-35" title="Permalink to this headline">#</a></h1>
<ul class="simple">
<li><p><strong>Comprehensiveness (10%)</strong></p>
<li><p><strong>Code Quality (15%)</strong> Quality and functionality of the scripts and code</p>
<ul>
<li><p>The code is clean, well-documented, and follows good programming practices</p></li>
<li><p>All scripts run without errors (when the environment is properly set up)</p></li>
<li><p>Code is modular, with reusable functions where appropriate</p></li>
<li><p>Scripts achieve the intended outcomes (e.g., generating plots, performing analysis)</p></li>
</ul>
</li>
<li><p><strong>Reproducibility (25%)</strong> Ease of reproducing the analysis and results</p>
<ul>
<li><p>Repository includes all three components: AI-ready data, CML, and DL.</p></li>
<li><p>Each component is complete and well-documented with code, results, and explanations.</p></li>
<li><p>The repository includes clear instructions (e.g., in a <a class="reference external" href="http://README.md">README.md</a>) for setting up the environment and running the code</p></li>
<li><p>Jupyter notebooks, scripts, and any other files necessary to recreate the analysis are provided</p></li>
<li><p>Data (or instructions to access data) are included or referenced appropriately</p></li>
<li><p>Output (plots, tables) are reproducible using the code</p></li>
</ul>
</li>
<li><p><strong>Reproducibility and Code Quality (10%)</strong></p>
<li><p><strong>Organization &amp; Structure (20%)</strong> Organization and clarity of the repository structure</p>
<ul>
<li><p>Code is modular, organized, and follows standard practices for AI/ML projects (e.g., using PyTorch for DL).</p></li>
<li><p>Instructions for reproducing results are clear (e.g., README with dependencies, instructions, and commands).</p></li>
<li><p>Repository is well-organized with clear folder structure (e.g., separate folders for code, data, results, etc.)</p></li>
<li><p>File and folder names are descriptive and intuitive</p></li>
<li><p><code class="docutils literal notranslate"><span class="pre">README</span></code> file provides a clear overview of the repository and how to navigate it</p></li>
</ul>
</li>
<li><p><strong>Integration and Documentation (10%)</strong></p>
<li><p><strong>Documentation (15%)</strong> Clarity and completeness of documentation</p>
<ul>
<li><p>Demonstrates integration across components with shared preprocessing steps, consistent evaluation metrics, and unified outputs.</p></li>
<li><p>Includes high-quality documentation that explains the project, methods, and findings holistically.</p></li>
<li><p>README file clearly explains the project, dependencies, and setup instructions</p></li>
<li><p>Code and notebooks are well-documented, including comments explaining key sections</p></li>
<li><p>Scripts include docstrings for functions and appropriate inline comments</p></li>
</ul>
</li>
<li><p><strong>Team Contributions (5%)</strong></p>
<li><p><strong>Environment Setup (10%)</strong> Provision of environment setup and dependency management</p>
<ul>
<li><p>Repository reflects contributions from all team members (e.g., clear commit history, attribution in code/comments).</p></li>
<li><p>Includes a complete and working conda environment file (<code class="docutils literal notranslate"><span class="pre">environment.yml</span></code>) or <code class="docutils literal notranslate"><span class="pre">requirements.txt</span></code> for virtual environments</p></li>
<li><p>Environment file lists all necessary dependencies with correct versions</p></li>
<li><p>Instructions for setting up the environment are clear and easy to follow</p></li>
</ul>
</li>
<li><p><strong>Version Control Practices (5%)</strong> Effective use of Git and GitHub features</p>
<ul>
<li><p>Commits are frequent, descriptive, and reflect the progression of the project.</p></li>
<li><p>Clear use of branches, if applicable (e.g., for different features or phases of the project)</p></li>
<li><p>Issues, pull requests, or other GitHub collaboration tools are used effectively.</p></li>
</ul>
</li>
</ul>
</section>
<hr class="docutils" />
<section id="presentation-10-minutes-25">
<h1><strong>3. Presentation (10 Minutes) - 25%</strong><a class="headerlink" href="#presentation-10-minutes-25" title="Permalink to this headline">#</a></h1>
<section id="presentation-10-15-minutes-25">
<h1><strong>3. Presentation (10-15 Minutes) - 25%</strong><a class="headerlink" href="#presentation-10-15-minutes-25" title="Permalink to this headline">#</a></h1>
<ul class="simple">
<li><p><strong>Content and Delivery (10%)</strong></p>
<li><p><strong>Content (20%)</strong> Quality and depth of research</p>
<ul>
<li><p>Present a clear statement of an outstanding research question</p></li>
<li><p>Provides evidence and reference to the scientific literature to support the key points</p></li>
<li><p>Present an AI-ready data set and preliminary analysis.</p></li>
<li><p>Demonstrate a classic machine learning example.</p></li>
<li><p>Demonstrates a deep learning example</p></li>
<li><p>Discuss the computational time for training and deploying</p></li>
<li><p>Discuss the appropriateness of computational resources needed</p></li>
</ul>
</li>
<li><p><strong>Structure and Organization (15%)</strong> Coherence and flow of the presentation</p>
<ul>
<li><p>Logical structure (report and presentation: intro, body, conclusion; software: readme, env file, src/, data/, plots/,…)</p></li>
<li><p>Key points are clearly distinguished and emphasized</p></li>
</ul>
</li>
<li><p><strong>Clarity and Delivery (20%)</strong> Effectiveness in communicating ideas</p>
<ul>
<li><p>Clear articulation and pronunciation</p></li>
<li><p>Adequate volume and pace</p></li>
<li><p>Minimal reliance on notes, maintaining eye contact with the audience</p></li>
<li><p>Confident and professional demeanor</p></li>
</ul>
</li>
<li><p><strong>Visual Aids (10%)</strong> Effectiveness of any supporting visual materials (slides, charts, plots)</p>
<ul>
<li><p>Visual aids enhance, not distract, from the presentation</p></li>
<li><p>Information is presented clearly, is easy to follow, and uses appropriate design principles</p></li>
<li><p>Slides do not overwhelm with text or complex visuals</p></li>
</ul>
</li>
<li><p><strong>Engagement and Interaction (10%)</strong> Ability to engage and interact with the audience</p>
<ul>
<li><p>Encourages audience interaction through questions or active participation</p></li>
<li><p>Responds effectively to audience questions and comments</p></li>
</ul>
</li>
<li><p><strong>Critical Thinking and Analysis (15%)</strong> Depth of analysis and reflection on the research topic</p>
<ul>
<li><p>Presentation provides a clear and engaging summary of the project, including objectives, methods, results, and key insights.</p></li>
<li><p>Demonstrates understanding of the methods and their relevance to the geoscientific problem.</p></li>
<li><p>Demonstrates original thinking and critical engagement with the research</p></li>
<li><p>Identifies limitations or future directions for research</p></li>
</ul>
</li>
<li><p><strong>Integration and Interpretation (10%)</strong></p>
<li><p><strong>Professionalism (10%)</strong> Overall, the professional quality of the presentation</p>
<ul>
<li><p>Focuses on the integration of all three components and the scientific conclusions derived from them.</p></li>
<li><p>Highlights key comparisons, domain-specific implications, and future directions.</p></li>
<li><p>Respect for time limits, prepared with material</p></li>
<li><p>Appropriate attire and a respectful manner.</p></li>
</ul>
</li>
<li><p><strong>Team Contributions (5%)</strong></p></li>
<li><p>A erstanding and contributions.</p></li>
</ul>
</section>
<hr class="docutils" />
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