portal launch

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-  <title>Portfolio Details</title>
+  <title>Resources</title>
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portfolio-details-1.html

@@ -88,7 +88,7 @@ <h1 class="text-light"><a href="index.html">Arun</a></h1>
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-          <h2>Machine learning</h2>
+          <h2>Machine Learning and Data Science</h2>
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             <li><a href="index.html#portfolio" class="clickable-box">Go to portfolio</a></li>
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@@ -129,10 +129,100 @@ <h2>Machine learning</h2>
           <h1>Machine learning</h1>
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+                <img src="assets/img/portfolio/CS-ml-deep.png" alt="" style="max-width: 30%; max-height: 30%;">
                 <figcaption style="text-align: center;"><strong>Image credit:</strong></figcaption>
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+
+          <section id="ML-1">
+            <h3>Introduction</h3>
+            Welcome to my portfolio, where I showcase my journey and expertise in the realms of Machine Learning, Deep Learning, and Statistical Fundamentals. Through rigorous exploration and practical projects, I've delved into diverse aspects of data science, contributing to my passion for unraveling the intricacies of artificial intelligence.
+            <p></p>
+            <h4>Topics Explored:</h4>
+            <ol>
+              <li><strong><a href="https://github.com/arunp77/Machine-Learning/tree/main/Deep-learning" target="_blank">Deep Learning and Neural Networks</a>: </strong>
+                <ul>
+                  <li>Explored the foundations and applications of deep learning, diving into neural network architectures, optimization algorithms, and cutting-edge frameworks like TensorFlow and PyTorch.</li>
+                  <li>Implemented and fine-tuned various neural networks for tasks such as image classification, natural language processing, and generative modeling.</li>
+                </ul>
+              </li>
+              <li><strong><a href="https://github.com/arunp77/Machine-Learning/tree/main/ML-Fundamental" target="_blank">Machine Learning Concepts</a>: </strong>
+                <ul>
+                  <li>Covered a spectrum of machine learning algorithms, from classic models like linear regression and decision trees to sophisticated ensemble methods.</li>
+                  <li>Applied machine learning techniques to real-world problems, leveraging the power of scikit-learn and other libraries.</li>
+                </ul>
+              </li>
+              <li><strong><a href="https://github.com/arunp77/Machine-Learning/tree/main/Statistics-fundamental" target="_blank">Statistical Theory</a>: </strong>
+                <ul>
+                  <li>Provided a solid grounding in statistical fundamentals, discussing both descriptive and inferential statistics.</li>
+                  <li>Explored the nuances of statistical hypothesis testing, confidence intervals, and probability distributions, establishing a robust statistical foundation for data analysis.</li>
+                </ul>
+              </li>
+            </ol>
+
+            <h3>Regression Modeling</h3>
+            <ul>
+              <li>Engaged in in-depth discussions on regression models, exploring their applications in predicting and understanding relationships between variables.</li>
+              <li>Implemented regression models in Python, demonstrating proficiency in translating theoretical concepts into practical solutions.</li>
+            </ul>
+
+
+            <h3><a href="https://github.com/arunp77/Machine-Learning/tree/main/Projects-ML" target="_blank">Projects: </a></h3>
+            <ul>
+              <li>Showcased practical application through hands-on projects, where I tackled real-world challenges using machine learning and data science techniques.</li>
+              <li>Leveraged Python to develop and deploy solutions, highlighting my ability to bridge the gap between theory and application.</li>
+            </ul>
+
+            <p>As you navigate through my portfolio, you'll find a blend of theoretical insights and hands-on experience, reflecting my dedication to continuous learning and innovation in the ever-evolving field of machine learning.</p>
+
+
+          </section>
+
+          <p>Thank you for visiting, and feel free to explore my projects and writings to get a glimpse into my journey through the realms of data science and artificial intelligence.</p>
+
+
+          <section id="ML-reference">
+            <h3>Reference</h3>
+            <ul>
+              <li>Machine learning using python, Manarajan Pradhan, U Dinesh Kumar</li>
+              <li>Please follow lecture series provided at <a href="https://jovian.ai/" target="_blank"> Jovian.ml</a>, i.e. <a href="https://jovian.ai/learn/data-analysis-with-python-zero-to-pandas" target="_blank">Data Analysis with Python: Zero to Pandas</a>.</li>
+              <li><a href="https://roadmap.sh/python/" target="_blank">Python roadmap</a></li>
+              <li><a href="https://www.w3schools.com/python/default.asp" target="_blank">Python tutorials at w3school</a></li>
+              <li><a href="https://github.com/asabeneh/30-days-of-python" target="_blank">30 Days of Python</a></li>
+              <li><a href="https://docs.python.org/3/tutorial/" target="_blank">Python official documents</a></li>
+              <li>Statistics, Murray R. Spiegel, Larry J. Stephens</li>
+            </ul>
+          </section>
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portfolio-details.html

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-  <title>Portfolio Details</title>
+  <title>EDA</title>
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