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fastapi – main framework uvicorn – ASGI server sqlalchemy/asyncpg – DB ORM/engine for PostgreSQL alembic – DB migrations psycopg2-binary – used for database CLI tasks by alembic (optional but handy) python-jose[cryptography], passlib[bcrypt] – for JWT and password security/auth python-dotenv – for environment variable management pydantic – for schema validation (required by FastAPI)

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People only know Kaggle data source 8 real-world data sources for your Machine Learning projects: 𝟭. 𝗦𝘁𝗿𝗮𝘁𝗮𝗦𝗰𝗿𝗮𝘁𝗰𝗵 → 49+ real business datasets → Actual interview-style problems → https://lnkd.in/dkscDjvQ 𝟮. 𝗨𝗖𝗜 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗥𝗲𝗽𝗼𝘀𝗶𝘁𝗼𝗿𝘆 → 653+ datasets, battle-tested → What researchers actually use → https://lnkd.in/dzCUAFpH 𝟯. 𝗔𝗪𝗦 𝗣𝘂𝗯𝗹𝗶𝗰 𝗗𝗮𝘁𝗮𝘀𝗲𝘁𝘀 → 494+ production-scale datasets → Learn cloud integration from day 1 → https://lnkd.in/dAqnJHjv 𝟰. 𝗪𝗼𝗿𝗹𝗱 𝗕𝗮𝗻𝗸 𝗢𝗽𝗲𝗻 𝗗𝗮𝘁𝗮 → Global economic/social data → Perfect for real-world impact projects → https://lnkd.in/dYu-m2PK 𝟱. 𝗗𝗮𝘁𝗮.𝗴𝗼𝘃 → 283K+ government datasets → 50+ formats, serious scale → https://data.gov/ 𝟲. 𝗚𝗼𝗼𝗴𝗹𝗲 𝗗𝗮𝘁𝗮𝘀𝗲𝘁 𝗦𝗲𝗮𝗿𝗰𝗵 → Academic + research data → Find what others can't → https://lnkd.in/d-ziT_3z 𝟳. 𝗢𝗽𝗲𝗻𝗠𝗟 → 5,400+ datasets with ML benchmarks → Compare your work to SOTA → https://www.openml.org/ 𝗕𝗼𝗻𝘂𝘀: 𝗞𝗮𝗴𝗴𝗹𝗲 → 274K+ datasets, can't deny the breadth → Just don't stop here → https://www.kaggle.com/