msanjeevkumar

#!/bin/bash

set -euo pipefail

# Directory setup
APP_DIR="${HOME}/Applications"
ICON_DIR="${HOME}/.local/share/icons"
DESKTOP_DIR="${HOME}/.local/share/applications"
BIN_DIR="${HOME}/.local/bin"

msanjeevkumar

{
    "basics": {
        "name": "Sanjeev Kumar",
        "label": "Senior Software Engineer",
        "image": "",
        "email": "[email protected]",
        "phone": "063011 14268",
        "url": "https://www.linkedin.com/in/sanjeevmsk",
        "summary": "Experienced Senior Software Engineer with a strong background in backend development and microservices architecture. Skilled in optimizing database performance, ensuring security compliance, and collaborating with cross-functional teams. Proven track record in delivering high-quality software solutions.",
        "location": {

msanjeevkumar

[{"id": "qdrant", "name": "Qdrant", "description": "Qdrant is a vector similarity search engine designed for storing, searching, and managing points along with their respective payloads. Built with an emphasis on extensive filtering, it is particularly beneficial for neural network matching, semantic-based matching, and faceted search. Qdrant offers various deployment options including local mode, on-premise server deployment, and Qdrant Cloud, each catering to different use-case scenarios. [Learn More](https://qdrant.tech/documentation/)", "documentation": "# \ud83d\udcd1 Documentation\n\n## \ud83d\udccc Description\n\n<a href='https://qdrant.tech/' target='_blank'>Qdrant</a> is a vector similarity search engine designed for storing, searching, and managing points along with their respective payloads. Built with an emphasis on extensive filtering, it is particularly beneficial for neural network matching, semantic-based matching, and faceted search. Qdrant offers various deployment options including local mo