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Rebuild FAQ for DataForSolution and OraDigit
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faq.html

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permalink: /faq/
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<section id="faq">
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<h1>❓ Frequently Asked Questions</h1>
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<p>Find answers to common questions about LLmachine, data science, and AI.</p>
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<!-- FAQ Section -->
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<div class="faq-list">
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<div class="faq-item">
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<h2>What is LLmachine?</h2>
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<div class="faq-answer">
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<p>LLmachine is a professional platform focused on delivering AI, data science, and analytics solutions. We help individuals and organizations access tools, tutorials, career preparation resources, and hands-on project experience in machine learning, analytics, and applied data science.</p>
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</div>
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</div>
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<div class="faq-item">
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<h2>How can I contact LLmachine?</h2>
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<div class="faq-answer">
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<p>You can reach us through the <a href="/contact/">Contact page</a> or email directly at <a href="mailto:kent.sew@gmail.com">kent.sew@gmail.com</a>. We respond within 24 hours to most inquiries.</p>
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</div>
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</div>
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<div class="faq-item">
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<h2>What services do you offer?</h2>
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<div class="faq-answer">
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<p>LLmachine provides a range of services tailored for data-driven environments, including:</p>
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<ul>
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<li>Advanced analytics and reporting</li>
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<li>AI/ML project development</li>
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<li>Healthcare and financial data consulting</li>
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<li>Strategic planning and dashboard creation</li>
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<li>Career readiness tools for aspiring data professionals</li>
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</ul>
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</div>
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</div>
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<section class="dfs-faq-hero">
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<div class="dfs-faq-shell">
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<p class="dfs-faq-kicker">DataForSolution by OraDigit Technology</p>
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<h1>Frequently Asked Questions</h1>
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<p>Clear answers about the platform, its relationship to OraDigit, its tools, learning resources, projects, and ways to connect.</p>
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</div>
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</section>
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<div class="faq-item">
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<h2>Where can I learn data science for free?</h2>
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<div class="faq-answer">
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<p>There are several high-quality free resources to begin your journey:</p>
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<ul>
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<li><a href="https://www.coursera.org/learn/machine-learning" target="_blank">Machine Learning by Stanford University (Coursera)</a></li>
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<li><a href="https://www.kaggle.com/learn" target="_blank">Kaggle Learn — Applied ML & Data Science Labs</a></li>
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<li><a href="https://scikit-learn.org/" target="_blank">Scikit-learn — Python ML Library Documentation</a></li>
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</ul>
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<p>We also provide our own toolkits and case-based projects through the <a href="/toolkits/">Toolkits section</a>.</p>
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</div>
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</div>
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</div>
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<section class="dfs-faq-section">
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<div class="dfs-faq-shell dfs-faq-list">
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<details open><summary>What is DataForSolution?</summary><div><p>DataForSolution is the learning, knowledge, tools, and applied-project product within the OraDigit Technology ecosystem. Its purpose is to help people learn data science, build responsible AI, and solve real problems through practical resources.</p></div></details>
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<details><summary>How is DataForSolution related to OraDigit Technology?</summary><div><p>OraDigit Technology is the broader healthcare technology, clinical informatics, analytics, research, and product ecosystem. DataForSolution supports that mission through education, working tools, technical knowledge, and project demonstrations.</p></div></details>
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<details><summary>Who is behind the platform?</summary><div><p>DataForSolution and OraDigit are founded by Lissan Liben (He/Him), whose professional focus includes Healthcare Business Intelligence, Clinical Informatics, Healthcare Analytics, Medical Imaging, Data Science, Software Engineering, and OraDigit Research.</p><p><a href="https://www.linkedin.com/in/lissan-analytic" target="_blank" rel="noopener noreferrer">View Lissan’s LinkedIn profile</a>.</p></div></details>
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<details><summary>What can I learn here?</summary><div><p>The platform develops structured learning and practical resources in data science, statistics, programming, analytics, artificial intelligence, healthcare technology, medical imaging, and software development.</p><p>Start from the <a href="{{ '/learn/' | relative_url }}">Learning Overview</a>.</p></div></details>
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<details><summary>Which tools are currently available?</summary><div><p>The Tool Lab contains working browser tools, notebooks, cheat sheets, and planned utilities. The CSV Data Profiler is currently available and processes files locally in the visitor’s browser.</p><p>Visit the <a href="{{ '/toolkits/' | relative_url }}">Tools Overview</a> or <a href="{{ '/free-tools/' | relative_url }}">Free Tools</a>.</p></div></details>
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<details><summary>Are uploaded files sent to a server?</summary><div><p>The CSV Data Profiler processes the selected file locally in the browser and does not intentionally upload it to DataForSolution. Each future tool will state its own privacy behavior clearly.</p></div></details>
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<details><summary>Does the platform provide medical advice?</summary><div><p>No. Healthcare and medical imaging content is educational and intended to support learning, workflow understanding, research, and technology development. It does not replace professional judgment, diagnosis, treatment, or an official clinical report.</p></div></details>
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<details><summary>Can organizations collaborate with OraDigit or DataForSolution?</summary><div><p>Yes. Relevant areas include healthcare business intelligence, clinical informatics, healthcare analytics, medical imaging, data science, software engineering, research, education, and responsible AI.</p><p>See the <a href="{{ '/collaborate/' | relative_url }}">Collaborate page</a>.</p></div></details>
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<details><summary>Can I contribute a project, tool, or article?</summary><div><p>Yes. Original and well-explained projects, tools, case studies, learning resources, and responsible AI work may be proposed for review through the <a href="{{ '/contribute/' | relative_url }}">Contribute page</a>.</p></div></details>
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<details><summary>How can I contact Lissan or the platform?</summary><div><p>Use the <a href="{{ '/contact/' | relative_url }}">Contact page</a>, connect through <a href="https://www.linkedin.com/in/lissan-analytic" target="_blank" rel="noopener noreferrer">LinkedIn</a>, or review public work on <a href="https://github.com/DataForSolution" target="_blank" rel="noopener noreferrer">GitHub</a>.</p></div></details>
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</div>
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</section>
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<!-- AI Chatbot -->
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<div id="faq-chatbot-container">
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<h2>💬 Ask Our AI-Powered Chatbot</h2>
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<p>Have more questions? Chat with our AI-powered assistant!</p>
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<div class="chat-container">
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<div id="faq-chat-display"></div>
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<div class="input-container">
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<input type="text" id="faq-chat-input" placeholder="Type your question...">
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<button id="faq-chat-submit">Ask</button>
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</div>
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</div>
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<section class="dfs-faq-section dfs-faq-section--soft">
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<div class="dfs-faq-shell">
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<h2>Continue exploring</h2>
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<div class="dfs-faq-links">
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<a href="{{ '/about/' | relative_url }}"><strong>About</strong><span>Understand the platform and founder.</span></a>
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<a href="{{ '/learn/' | relative_url }}"><strong>Learn</strong><span>Follow structured learning paths.</span></a>
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<a href="{{ '/toolkits/' | relative_url }}"><strong>Tools</strong><span>Use practical resources.</span></a>
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<a href="https://www.oradigit.com" target="_blank" rel="noopener noreferrer"><strong>OraDigit</strong><span>Explore the wider technology ecosystem.</span></a>
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</div>
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</div>
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</section>
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<!-- Recommended Resources -->
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<div id="recommendation">
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<h2>🔗 Recommended for You</h2>
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<p>Explore related resources:</p>
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<ul id="recommendation-list"></ul>
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</div>
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<script type="application/ld+json">
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{
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"@context": "https://schema.org",
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"@type": "FAQPage",
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"mainEntity": [
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{
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"@type": "Question",
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"name": "How do I start with Machine Learning?",
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"acceptedAnswer": {
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"@type": "Answer",
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"text": "Start by learning Python, NumPy, Pandas, and try hands-on projects using Jupyter notebooks available on LLmachine."
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}
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},
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{
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"@type": "Question",
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"name": "What is LLmachine?",
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"acceptedAnswer": {
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"@type": "Answer",
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"text": "LLmachine is a learning hub for AI, data science, and analytics offering projects, tutorials, eBooks, and career tools for students and professionals."
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}
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},
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{
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"@type": "Question",
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"name": "Can I contribute to the platform?",
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"acceptedAnswer": {
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"@type": "Answer",
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"text": "Yes! Visit the 'Write for Us' page to submit tutorials, projects, or insights and get featured."
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}
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}
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]
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}
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{"@context":"https://schema.org","@type":"FAQPage","mainEntity":[{"@type":"Question","name":"What is DataForSolution?","acceptedAnswer":{"@type":"Answer","text":"DataForSolution is the learning, knowledge, tools, and applied-project product within the OraDigit Technology ecosystem."}},{"@type":"Question","name":"How is DataForSolution related to OraDigit Technology?","acceptedAnswer":{"@type":"Answer","text":"OraDigit Technology is the broader healthcare technology and research ecosystem, while DataForSolution supports its mission through education, tools, knowledge, and projects."}},{"@type":"Question","name":"Who is behind the platform?","acceptedAnswer":{"@type":"Answer","text":"DataForSolution and OraDigit are founded by Lissan Liben, whose work spans healthcare business intelligence, clinical informatics, healthcare analytics, medical imaging, data science, software engineering, and OraDigit Research."}}]}
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</script>
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</section>
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<style>
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/* FAQ Styling */
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#faq {
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padding: 50px 20px;
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text-align: center;
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background: #1e1e1e; /* Dark background */
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color: #ffffff; /* White text */
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}
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.faq-list {
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max-width: 800px;
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margin: auto;
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text-align: left;
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}
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.faq-item {
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padding: 15px;
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background: #2c2c2c;
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border-radius: 10px;
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box-shadow: 0 4px 8px rgba(0, 0, 0, 0.4);
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cursor: pointer;
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margin-bottom: 10px;
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color: white;
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}
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.faq-item h2 {
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font-size: 1.2em;
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color: #00aaff;
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}
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.faq-answer {
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display: none;
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margin-top: 10px;
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background-color: #1e1e1e;
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padding: 10px;
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border-radius: 5px;
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transition: all 0.3s ease;
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}
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/* Ensure text inside .faq-answer is white */
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.faq-answer,
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.faq-answer * {
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color: #ffffff !important;
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}
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.faq-item.active .faq-answer {
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display: block;
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}
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/* Chatbot Styling */
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.chat-container {
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display: flex;
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flex-direction: column;
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align-items: center;
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margin: 20px auto;
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max-width: 600px;
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border: 1px solid #444;
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border-radius: 10px;
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padding: 15px;
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background: #2c2c2c;
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color: white;
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}
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#faq-chat-display {
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max-height: 300px;
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overflow-y: auto;
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border: 1px solid #666;
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padding: 10px;
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margin-bottom: 15px;
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width: 100%;
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border-radius: 5px;
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background: #1a1a1a;
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color: #ffffff;
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}
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.input-container {
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display: flex;
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gap: 10px;
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width: 100%;
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}
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.input-container input {
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flex: 1;
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padding: 10px;
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border: 1px solid #555;
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border-radius: 5px;
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background: #333;
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color: white;
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}
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.input-container button {
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padding: 10px 15px;
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background-color: #007BFF;
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color: white;
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border: none;
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border-radius: 5px;
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cursor: pointer;
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}
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.input-container button:hover {
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background-color: #0056b3;
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}
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/* Recommendations */
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#recommendation ul {
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list-style: none;
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padding: 0;
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text-align: left;
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max-width: 600px;
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margin: auto;
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color: white;
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}
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#recommendation li {
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margin: 10px 0;
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}
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#recommendation a {
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color: #00aaff;
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text-decoration: none;
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}
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#recommendation a:hover {
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color: #ffffff;
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text-decoration: underline;
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}
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</style>
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<script>
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// FAQ Toggle Logic
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document.addEventListener('click', (e) => {
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const faqItem = e.target.closest('.faq-item');
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if (faqItem) {
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faqItem.classList.toggle('active');
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}
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});
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// Chatbot Logic
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document.getElementById("faq-chat-submit").addEventListener("click", async () => {
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const input = document.getElementById("faq-chat-input").value.trim();
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const display = document.getElementById("faq-chat-display");
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if (!input) return;
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const userMessage = document.createElement("p");
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userMessage.innerHTML = `<strong>You:</strong> ${input}`;
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display.appendChild(userMessage);
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try {
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const response = await fetch("http://localhost:3000/faq-chat", {
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method: "POST",
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headers: { "Content-Type": "application/json" },
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body: JSON.stringify({ question: input })
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});
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const data = await response.json();
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const botMessage = document.createElement("p");
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botMessage.innerHTML = `<strong>Bot:</strong> ${data.answer || "I'm sorry, I don't have an answer for that."}`;
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display.appendChild(botMessage);
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} catch (error) {
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console.error("Error:", error);
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const botMessage = document.createElement("p");
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botMessage.innerHTML = `<strong>Bot:</strong> Unable to process your request right now.`;
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display.appendChild(botMessage);
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}
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document.getElementById("faq-chat-input").value = "";
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});
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// Recommendations
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document.addEventListener("DOMContentLoaded", () => {
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const recommendationList = document.getElementById("recommendation-list");
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const recommendations = [
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{ title: "Getting Started with AI", url: "/blog/ai-intro" },
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{ title: "Learn About Our Data Science Projects", url: "/projects" },
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{ title: "Check Out Our Services", url: "/services" },
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];
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recommendations.forEach(item => {
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const listItem = document.createElement("li");
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listItem.innerHTML = `<a href="${item.url}">${item.title}</a>`;
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recommendationList.appendChild(listItem);
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});
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});
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</script>
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.dfs-faq-hero,.dfs-faq-section{padding:68px 22px}.dfs-faq-hero{background:linear-gradient(135deg,#0f172a,#164e63 55%,#14532d);color:#fff}.dfs-faq-shell{max-width:960px;margin:0 auto}.dfs-faq-kicker{text-transform:uppercase;letter-spacing:.12em;font-size:.78rem;font-weight:800;color:#bbf7d0}.dfs-faq-hero h1{color:#fff;font-size:clamp(2.3rem,5vw,4rem)}.dfs-faq-hero p{color:#e2e8f0;line-height:1.8}.dfs-faq-list details{background:#fff;border:1px solid #e2e8f0;border-radius:14px;margin:0 0 14px;box-shadow:0 8px 22px rgba(15,23,42,.05)}.dfs-faq-list summary{cursor:pointer;padding:20px 22px;font-weight:800;color:#0f172a}.dfs-faq-list details div{padding:0 22px 20px;color:#334155;line-height:1.7}.dfs-faq-list a{color:#15803d;font-weight:700}.dfs-faq-section--soft{background:#f1f5f9}.dfs-faq-links{display:grid;grid-template-columns:repeat(4,1fr);gap:16px}.dfs-faq-links a{display:block;background:#fff;border:1px solid #e2e8f0;border-radius:14px;padding:20px;text-decoration:none;color:inherit}.dfs-faq-links strong,.dfs-faq-links span{display:block}.dfs-faq-links strong{color:#15803d;margin-bottom:7px}.dfs-faq-links span{color:#475569;line-height:1.5}@media(max-width:760px){.dfs-faq-links{grid-template-columns:1fr 1fr}}@media(max-width:480px){.dfs-faq-links{grid-template-columns:1fr}}
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</style>

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