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jaansiparsajaansiparsa
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spring 2026 index
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‎.ruby-version‎

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3.2.2

‎Gemfile.lock‎

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just-the-docs (= 0.10.0)
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BUNDLED WITH
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2.5.15
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2.5.15

‎docs/archive/facilitators.md‎

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---
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title: Facilitators
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parent: Archive
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permalink: /archive/facilitators/
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nav_order: 4
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layout: default
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---
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[← Archive home]({{ site.baseurl }}/archive/)
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<style>
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.role {
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display: flex;
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flex-wrap: wrap;
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margin-bottom: 2rem;
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}
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.person {
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display: flex;
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flex-basis: 45%;
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padding: 0.75rem;
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margin-bottom: 0.75rem;
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border: 1px solid #e1e4e8;
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border-radius: 8px;
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background-color: #ffffff;
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transition: box-shadow 0.2s ease;
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}
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.person:hover {
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box-shadow: 0 2px 8px rgba(0, 0, 0, 0.1);
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}
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.person-image {
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border-radius: 50%;
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height: 120px;
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width: 120px;
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margin-right: 0.75rem;
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object-fit: cover;
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flex-shrink: 0;
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}
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.person-name {
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margin: 0.25rem 0;
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font-size: 1rem;
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font-weight: 600;
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color: #397DFF;
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}
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.person-name a {
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color: #397DFF;
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text-decoration: none;
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}
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.person-name a:hover {
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text-decoration: underline;
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}
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.person-role {
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font-weight: 500;
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color: #397DFF;
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margin: 0.25rem 0;
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font-size: 0.9rem;
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}
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.person p {
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margin: 0.25rem 0;
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line-height: 1.4;
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font-size: 0.85rem;
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}
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@media (max-width: 768px) {
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.person {
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flex-direction: column;
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text-align: center;
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padding: 0.75rem;
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flex-basis: 100%;
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}
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.person-image {
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margin-right: 0;
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margin-bottom: 0.5rem;
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}
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.role {
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flex-direction: column;
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}
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}
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</style>
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# <span style="color: #397DFF; font-weight: 350">Facilitators</span>
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Running CRUP would not be possible without these amazing people!
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<div class="role">
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{% assign edvps = site.people | where: 'role', 'VP of Education' %}
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{% for person in edvps %}
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{{ person }}
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{% endfor %}
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</div>
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<div class="role">
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{% assign others = site.people | where_exp: 'person', 'person.role != "VP of Education"' %}
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{% for person in others %}
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{{ person }}
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{% endfor %}
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</div>

‎docs/archive/final_project.md‎

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---
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title: Final Project
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parent: Archive
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permalink: /archive/final_project/
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nav_order: 3
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layout: default
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---
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[← Archive home]({{ site.baseurl }}/archive/)
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# <span style="color: #397DFF; font-weight: 350">CRUP Fall 2025 Final Project</span>
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## <span style="color: #397DFF">Project Overview</span>
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You will design and execute a complete Machine Learning project that answers a real-world question and present your findings through an interactive website. This project integrates both machine learning and software engineering skills.
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## <span style="color: #397DFF">Core Requirements</span>
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- Formulate a specific, real-world problem that can be solved with **Machine Learning**
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- Build and train an **ML model** using a real dataset
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- Create an **interactive website** that explains your process and allows users to interact with your model
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---
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# <span style="color: #397DFF; font-weight: 350">Part A: Machine Learning Component</span>
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## <span style="color: #397DFF">1. Problem Formulation & Dataset Selection</span>
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Your task is to identify a clear, answerable question that requires machine learning to solve.
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### Dataset Requirements
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- Must come from a real dataset (e.g., **Kaggle**, **Hugging Face**)
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- Your project must be one of the following:
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- **Classification** (e.g., "Will this customer churn?")
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- **Regression** (e.g., "What will this house sell for?")
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---
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## <span style="color: #397DFF">2. Complete ML Pipeline Implementation</span>
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You must implement all stages of a professional ML workflow.
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### a) Data Acquisition and Cleaning
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- Download and load your dataset
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- Perform **Exploratory Data Analysis (EDA)** with visualizations and summary statistics
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- Handle missing values (remove, impute, etc.)
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- Encode categorical variables (e.g., one-hot encoding or label encoding)
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### b) Model Training and Hyperparameter Tuning
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- Try multiple models appropriate for your task
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- Train each model
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- Tune hyperparameters using **Grid Search**, **Random Search**, etc.
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### c) Rigorous Model Evaluation
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#### For Classification
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- **F1 Score**
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- **AUC**
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- **Accuracy** (use carefully)
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- **Confusion Matrix**
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#### For Regression
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- **R-squared (R²)**
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- **MAE**
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- **RMSE**
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### d) Artifact Preservation
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- Save your trained model (e.g., using `pickle` or `torch.save`)
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- You will load this model into your website
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---
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# <span style="color: #397DFF; font-weight: 350">Part B: Software Engineering Component</span>
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## <span style="color: #397DFF">1. Public-Facing Website</span>
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- Built using **React**
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- Serves as documentation + interactive demonstration
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## <span style="color: #397DFF">2. Required Website Content (Documentation)</span>
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### a) Central Problem & Real-World Impact
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Explain:
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- What question you're answering
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- Why it matters
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- Who benefits
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- What real-world decisions your model could influence
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### b) Data Source & Nature
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Include:
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- Dataset link
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- What each row represents
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- Features included
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- Number of examples
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- Any limitations or biases
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### c) ML Methodology
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Clarify:
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- Which algorithms you tried
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- Which you chose
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- Why you chose it
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- What hyperparameters you tuned
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### d) Final Performance Metrics
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Report:
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- Your final evaluation metrics
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- A direct answer to your core question
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- Limitations + failure modes
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---
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# <span style="color: #397DFF; font-weight: 350">3. Interactive Component (MANDATORY)</span>
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Your website must include at least **one interactive ML-powered element**.
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### Acceptable Options
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- **Prediction Form** (user enters input → model predicts)
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- **Slider-Based Dynamic Prediction**
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- **Interactive Visualizations**
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- **Comparative Predictions (What-if Analysis)**
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---
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# <span style="color: #397DFF; font-weight: 350">Part C: Deadlines & Deliverables</span>
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## <span style="color: #397DFF">📅 Deadlines</span>
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- **Research Proposal** — *Due: End of Thanksgiving Break*
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- One paragraph
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- Includes central question, dataset, and approach
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- **Final Project** — *Due: Before Banquet*
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- Full ML pipeline
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- Fully functional website
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- Complete documentation
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## <span style="color: #397DFF">✅ Deliverables Checklist</span>
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- [ ] **Research Proposal**
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- [ ] **ML Solution**
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- Dataset acquired & cleaned
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- Multiple models compared
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- Best model selected
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- Model evaluated
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- Model saved
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- [ ] **Website Component**
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- React website (public-facing)
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- Full documentation
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- At least one interactive component
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- Accessible, clear design
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---
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# <span style="color: #397DFF; font-weight: 350">🌟 Exemplary Projects for Inspiration</span>
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- https://llm-attacks.org
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- https://thinkingmachines.ai/blog/modular-manifolds
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- Distill-style explorations:
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- Feature Visualization
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- Activation Atlas
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- Handwriting with Neural Networks
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- Building Blocks of Interpretability
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- https://distill.pub
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---
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# <span style="color: #397DFF; font-weight: 350">Tips for Success</span>
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- Choose a **focused** question
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- Select a **manageable dataset**
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- Document continuously
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- Build the interactive component early
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- Make explanations accessible to non-ML audiences
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Good luck! 🚀

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