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solutions.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>ML-Scope Solutions</title>
<style>
:root {
--dark-blue: #1a365d;
--light-blue: #7db0e8;
--orange: #ff6b35;
}
body {
font-family: Arial, sans-serif;
line-height: 1.6;
color: var(--dark-blue);
margin: 0;
padding: 0;
background-color: #f0f8ff;
}
.container {
max-width: 800px;
margin: 0 auto;
padding: 20px;
}
nav {
background-color: var(--dark-blue);
padding: 10px 0;
}
nav .container {
display: flex;
justify-content: space-between;
align-items: center;
}
.logo {
width: 50px;
height: 50px;
}
.nav-links a {
color: white;
text-decoration: none;
margin-left: 20px;
}
.nav-links a:hover {
color: var(--light-blue);
}
h1 {
text-align: center;
color: var(--dark-blue);
}
.project-container {
border: 1px solid var(--light-blue);
margin-bottom: 20px;
border-radius: 5px;
overflow: hidden;
background-color: white;
}
.project-header {
background-color: var(--light-blue);
padding: 10px;
cursor: pointer;
display: flex;
justify-content: space-between;
align-items: center;
transition: background-color 0.3s ease;
}
.project-header:hover {
background-color: #6a9fd4;
}
.project-header h2 {
margin: 0;
color: var(--dark-blue);
}
.project-content {
display: none;
padding: 20px;
}
.project-content.active {
display: block;
}
.toggle-icon::after {
content: "\25BC";
color: var(--dark-blue);
}
.project-header.active .toggle-icon::after {
content: "\25B2";
}
a {
color: var(--orange);
text-decoration: none;
}
a:hover {
text-decoration: underline;
}
</style>
</head>
<body>
<nav>
<div class="container">
<a href="index.html">
<img src="aida-logo.jpeg" alt="Logo" class="logo" />
</a>
<div class="nav-links">
<a href="index.html">Problems</a>
<a href="solutions.html">Solutions</a>
<a href="leaderboard.html">Leaderboard</a>
<a href="resources.html">Resources</a>
</div>
</div>
</nav>
<div class="container">
<h1>Solutions</h1>
<div id="content"></div>
</div>
<center><h2>None Yet :(</h2></center>
<script>
const solutionsData = [];
// const solutionsData = [
// {
// project: 1,
// title: "House Price Prediction Solution",
// content: `
// <h1>Project 1 Solutions</h1>
// <h2>Summary</h2>
// <h4>Baseline Models:</h4>
// <ul>
// <li>Linear Regression yielded an R² score of 0.71, which is a reasonable baseline, but not highly accurate for predicting house prices.</li>
// <li>Decision Tree Classifier performed very poorly with a score of 0.0096, indicating it's unsuitable for this regression task.</li>
// <li>Random Forest Regressor achieved a significantly better score of 0.84, making it the best among the baseline models.</li>
// </ul>
// <h4>Highest-Performing Solutions:</h4>
// <ul>
// <li>Gradient Boosting Regressor after tuning hyperparameters (max_depth=5, n_estimators=200) scored 0.90, showing that ensemble methods with boosting can yield very strong results.</li>
// <li>Random Forest Regressor (with 500 estimators) performed similarly, with a score of 0.89, demonstrating that increasing the number of trees from 100 to 500 provided a marginal improvement.</li>
// </ul>
// <h4>Takeaways:</h4>
// <ul>
// <li>Feature Scaling and hyperparameter tuning were essential for achieving high accuracy.</li>
// <li>Ensemble methods like Random Forest and Gradient Boosting Regressor consistently outperformed linear models.</li>
// <li>Grid search allowed further refinement of hyperparameters, slightly improving the model's performance.</li>
// </ul>
// <a target="_blank" href="https://colab.research.google.com/drive/1u9JW5vECvlZ6huyvz7xrhJj2HmDrlmb_?authuser=5#scrollTo=nsSyl5JME8nn">Link to Notebook</a>
// <br>
// <a target="_blank" href="https://docs.google.com/presentation/d/1qy1OWxAyliL4PSqrljxphXdFPLurtd8j52xF4pKdMwA/edit?usp=sharing">Link to Slides</a>
// `,
// },
// {
// project: 2,
// title: "Heart Disease Classification Solution",
// content: `
// <h1>Project 2 Solutions</h1>
// <h2>Summary</h2>
// <h4>Baseline Models:</h4>
// <ul>
// <li>Stochastic Gradient Descent Classifier (with log loss) yielded an accuracy of 0.72, providing a reasonable starting point but not highly reliable for medical predictions.</li>
// <li>Random Forest Classifier achieved a much higher accuracy of 0.98, making it significantly better for classifying heart disease compared to SGD.</li>
// </ul>
// <h4>Highest-Performing Solutions:</h4>
// <ul>
// <li>Random Forest Classifier (with 100 estimators) was the top-performing model, reaching an accuracy of 0.98, indicating that ensemble methods are highly effective for this task.</li>
// </ul>
// <h4>Takeaways:</h4>
// <ul>
// <li>Random Forest outperformed linear classifiers, suggesting that decision tree-based models handle complex medical data better.</li>
// <li>Increasing the number of trees in the forest can lead to more robust predictions, particularly when dealing with health-related datasets.</li>
// <li>Future improvements could include exploring hyperparameter tuning and other advanced ensemble methods.</li>
// </ul>
// <a target="_blank" href="https://colab.research.google.com/drive/1TfhmyyxZ1njcXTghnxJuNAkaBVo-lWFW?usp=sharing">Link to Notebook</a>
// <br>
// <a target="_blank" href="https://docs.google.com/presentation/d/1ruvhrehQhAcr20RiEG_G6QNCvhQivFFeYbJUNscfafg/edit?usp=sharing">Link to Slides</a>
// `,
// },
// ];
function createProjectElement(projectData) {
const projectElement = document.createElement("div");
projectElement.className = "project-container";
projectElement.innerHTML = `
<div class="project-header">
<h2>Project ${projectData.project}: ${projectData.title}</h2>
<span class="toggle-icon"></span>
</div>
<div class="project-content">
${projectData.content}
</div>
`;
return projectElement;
}
function toggleProject(projectHeader) {
projectHeader.classList.toggle("active");
const content = projectHeader.nextElementSibling;
content.classList.toggle("active");
}
function loadContent(data) {
const contentDiv = document.getElementById("content");
contentDiv.innerHTML = "";
data.forEach((project, index) => {
const projectElement = createProjectElement(project);
contentDiv.appendChild(projectElement);
const projectHeader = projectElement.querySelector(".project-header");
projectHeader.addEventListener("click", () =>
toggleProject(projectHeader)
);
// Open the last project by default
if (index === data.length - 1) {
toggleProject(projectHeader);
}
});
}
// Determine which page to load based on the current URL
const currentPage = window.location.pathname.includes("solutions.html")
? "solutions"
: "problems";
loadContent(currentPage === "solutions" ? solutionsData : problemsData);
</script>
</body>
</html>