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CDA Seals Office of Green Homes Islamabad

The Capital Development Authority (CDA) has ordered the sealing of the marketing and site offices of Green Homes/Valley on Karor … Read More The post CDA Seals Office of Green Homes Islamabad appeared first on ProPakistani .

CDA Seals Office of Green Homes Islamabad

We haven't written up this one. ProPakistani has the full story — the link below goes straight to it.

Read the original at propakistani.pk →

More in Tech

Understanding Word Embeddings: How Machines Learn the Meaning of Words

When I started learning Natural Language Processing (NLP), one question kept coming back to me: How can a computer understand words when words are just text?

  • Word embeddings represent words as numerical vectors for computers to understand word relationships.
  • Word2Vec limitations include reliance on training corpus quality and potential bias inheritance.

Not the 90s?

Oh, yeah, those were the days? No, the 1990s weren’t better. We devs weren’t better, the users weren’t better, and, hell, payment wasn’t better.

  • Developers in the 90s faced tool and system shortcomings
  • Users appreciated improvements that enhanced experience
  • Current approach relies on prompting, potentially leading to suboptimal solutions

Curate Verifiable ActiveAdmin 4 Themes with Markdown and CI

When a Rails theme claims ActiveAdmin 4 support, the difficult part is often not finding a screenshot. It is checking whether the theme actually targets ActiveAdmin 4's Tailwind-based asset model…

  • Curated directory of ActiveAdmin 4 themes
  • Repository focuses on documentation and links
  • GitHub Actions ensures Markdown validity

I Tried to Teach a Computer "Apple" (It Thought It Was a Fruit, an iPhone, and a Vector)

Hello, DEV Community! 🙌 It’s my first time writing here. As I was studying how models handle text today, I ran into a funny realization: computers don't understand human words at all.

  • Computers understand language through numbers, not words
  • Word embedding represents words as points in a high-dimensional space
  • Mathematical operations on word vectors reveal semantic relationships

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