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    <id>https://stackdhruv.com/</id>
    <title>Dhruvkumar Patel</title>
    <updated>2026-05-12T17:20:37.689Z</updated>
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    <subtitle>The personal portfolio of Dhruvkumar Patel — Data Scientist Intern at Myntra, Graduate Researcher at IIIT Delhi's MIDAS Lab, with expertise in machine learning, multimodal AI, and full-stack development.</subtitle>
    <rights>All rights reserved 2026, Dhruvkumar Patel</rights>
    <entry>
        <title type="html"><![CDATA[Build Process: Advanced ANPR & Face Recognition for KAVACH-23]]></title>
        <id>https://stackdhruv.com/blog/advanced-anpr-details</id>
        <link href="https://stackdhruv.com/blog/advanced-anpr-details"/>
        <updated>2025-05-21T00:00:00.000Z</updated>
        <summary type="html"><![CDATA[A behind-the-scenes look at our national finalist project for the KAVACH-23 Cybersecurity Hackathon, covering data collection with local police, developing a high-accuracy YOLOv8 model, and building a cross-platform mobile app.]]></summary>
        <category label="Computer Vision" term="Computer Vision"/>
        <category label="PyTorch" term="PyTorch"/>
        <category label="YOLO" term="YOLO"/>
        <category label="React Native" term="React Native"/>
        <category label="Hackathon" term="Hackathon"/>
        <category label="ANPR" term="ANPR"/>
    </entry>
    <entry>
        <title type="html"><![CDATA[Building Idempotent Feature Pipelines in Databricks]]></title>
        <id>https://stackdhruv.com/blog/databricks-idempotent-pipelines</id>
        <link href="https://stackdhruv.com/blog/databricks-idempotent-pipelines"/>
        <updated>2026-05-10T00:00:00.000Z</updated>
        <summary type="html"><![CDATA[A practical pattern for snapshot-based, idempotent feature pipelines in Databricks — how to structure Delta tables so reruns never corrupt your training data.]]></summary>
        <category label="Databricks" term="Databricks"/>
        <category label="PySpark" term="PySpark"/>
        <category label="Delta Lake" term="Delta Lake"/>
        <category label="ML Engineering" term="ML Engineering"/>
        <category label="Feature Pipelines" term="Feature Pipelines"/>
        <category label="MLOps" term="MLOps"/>
    </entry>
    <entry>
        <title type="html"><![CDATA[Benchmarking the Death Star: A Deep Dive into Microservices Performance]]></title>
        <id>https://stackdhruv.com/blog/deathstar-benchmark</id>
        <link href="https://stackdhruv.com/blog/deathstar-benchmark"/>
        <updated>2025-05-24T00:00:00.000Z</updated>
        <summary type="html"><![CDATA[An inside look at our course project where we deployed, benchmarked, and monitored a complex microservices application on Docker Swarm and Kubernetes to understand real-world performance trade-offs.]]></summary>
        <category label="Microservices" term="Microservices"/>
        <category label="Kubernetes" term="Kubernetes"/>
        <category label="Docker" term="Docker"/>
        <category label="Prometheus" term="Prometheus"/>
        <category label="GKE" term="GKE"/>
        <category label="Observability" term="Observability"/>
    </entry>
    <entry>
        <title type="html"><![CDATA[From Chaos to Centralized: The Story of Drive Material LDRP]]></title>
        <id>https://stackdhruv.com/blog/driver-material-ldrp</id>
        <link href="https://stackdhruv.com/blog/driver-material-ldrp"/>
        <updated>2025-05-22T00:00:00.000Z</updated>
        <summary type="html"><![CDATA[How a simple hobby project to organize scattered class notes became an essential tool for thousands of students, achieving over 3,000 visits in its first week and a top Google ranking.]]></summary>
        <category label="Web Development" term="Web Development"/>
        <category label="Hobby Project" term="Hobby Project"/>
        <category label="SEO" term="SEO"/>
        <category label="Problem Solving" term="Problem Solving"/>
    </entry>
    <entry>
        <title type="html"><![CDATA[MCP Agents for ML Experiment Automation: A Practical Pattern]]></title>
        <id>https://stackdhruv.com/blog/mcp-agents-ml-automation</id>
        <link href="https://stackdhruv.com/blog/mcp-agents-ml-automation"/>
        <updated>2026-05-12T00:00:00.000Z</updated>
        <summary type="html"><![CDATA[How to use Model Context Protocol (MCP) agents to automate ML experiment workflows across Databricks, GitHub, and Grafana — turning repetitive experiment cycles into a single prompt.]]></summary>
        <category label="MCP" term="MCP"/>
        <category label="Agents" term="Agents"/>
        <category label="MLOps" term="MLOps"/>
        <category label="Databricks" term="Databricks"/>
        <category label="Automation" term="Automation"/>
        <category label="ML Engineering" term="ML Engineering"/>
    </entry>
    <entry>
        <title type="html"><![CDATA[Classifying Mental Health in Memes: A Multimodal Approach]]></title>
        <id>https://stackdhruv.com/blog/mental-health-meme-classification</id>
        <link href="https://stackdhruv.com/blog/mental-health-meme-classification"/>
        <updated>2025-05-23T00:00:00.000Z</updated>
        <summary type="html"><![CDATA[A deep dive into our NLP course project where we used Vision-Language Models to classify signs of anxiety and depression in internet memes, blending humor with serious analysis.]]></summary>
        <category label="NLP" term="NLP"/>
        <category label="Multimodal AI" term="Multimodal AI"/>
        <category label="PyTorch" term="PyTorch"/>
        <category label="Hugging Face" term="Hugging Face"/>
        <category label="Mental Health" term="Mental Health"/>
        <category label="Streamlit" term="Streamlit"/>
    </entry>
    <entry>
        <title type="html"><![CDATA[Build Process: Student Dropout Analysis]]></title>
        <id>https://stackdhruv.com/blog/student-dropout-analysis</id>
        <link href="https://stackdhruv.com/blog/student-dropout-analysis"/>
        <updated>2025-05-20T00:00:00.000Z</updated>
        <summary type="html"><![CDATA[A detailed breakdown of our award-winning project at the SSIP-22 State Level Hackathon, from data collection and dashboarding to predictive modeling and an IEEE publication.]]></summary>
        <category label="Python" term="Python"/>
        <category label="Machine Learning" term="Machine Learning"/>
        <category label="Data Visualization" term="Data Visualization"/>
        <category label="Hackathon" term="Hackathon"/>
        <category label="IEEE" term="IEEE"/>
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