The only reason why everyone prefers python

10/ No OCR → no automation. No automation → no scale.

9/ OCR turns pixels into text. NLP turns text into meaning.

8/ That’s why modern OCR combines: Computer Vision + Machine Learning + Language Models.

7/ The real challenge isn’t reading text. It’s reading messy, real-world text.

6/ Hospitals use OCR to digitize: • Prescriptions • Medical reports • Patient records.

5/ Traffic cameras don’t just see plates. OCR reads them in milliseconds.

4/ E-commerce platforms use OCR for: • Invoice matching • Order verification • Fraud detection.

3/ Banks use OCR to process: • Cheques • Loan forms • Statements at massive scale.

2/ KYC systems rely on OCR to extract: • Name • Date of birth • ID numbers in seconds.

1/ Every document you upload — PDF, scan, or photo — OCR reads it first.

OCR in the real world. 🧵

Padhai ke us stage pr hu k agar koi questions leak bhi karde toh bhi padhne ka mann nahi karega.

My new laptop 💻😂

Christmas 2025 falls on 25/12/25 — a rare moment where the day matches the year 🎄

• Programming runs on math • Logic comes from math • Algorithms depend on math • Data structures use math • AI models are built with math • Machine learning uses math • Deep learning relies on math • Linear algebra powers math-heavy systems • Probability drives decisions

Me every time in exams

RAG didn’t replace fine-tuning. It replaced bad memory. Models were never the problem. Context was. That’s why most “AI apps” fail without good retrieval.

Ek din code yahi reh jayega aur mai run ho jaunga

From ABCD to DBMS From Oops! to OOPS From ESSAY to DSA From Arey! to ARRAY From MISTAKE to ERROR "We all grew up"