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http://t.me/codeprogrammer
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🎁 Lisa has given away over $100,000 in the last 30 days. Every single one of her subscribers is making money.
She is a professional trader and broadcasts her way of making money trading on her channel EVERY subscriber she has helped, and she will help you.
🧠 Do this and she will help you earn :
1. Subscribe to her channel
2. Write “GIFT” to her private messages
3. Follow her channel and trade with her. Repeat transactions after her = earn a lot of money.
Subscribe 👇🏻
https://t.me/+DRO5evATod00NGIx
She is a professional trader and broadcasts her way of making money trading on her channel EVERY subscriber she has helped, and she will help you.
🧠 Do this and she will help you earn :
1. Subscribe to her channel
2. Write “GIFT” to her private messages
3. Follow her channel and trade with her. Repeat transactions after her = earn a lot of money.
Subscribe 👇🏻
https://t.me/+DRO5evATod00NGIx
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http://t.me/codeprogrammer
The Transformer's encoder clearly explained
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http://t.me/codeprogrammer
The Transformer's decoder clearly explained
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http://t.me/codeprogrammer
The Transformers architecture clearly explained
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Recurrent Neural Network (RNN) by hand ✍️ Excel
📂 Tags: #python #ML #RNN
http://t.me/codeprogrammer⭐️
Download Excel file👇
https://t.me/+Tdshx2j5cZ00N2Ji
http://t.me/codeprogrammer
Download Excel file
https://t.me/+Tdshx2j5cZ00N2Ji
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Categorical data encoding techniques, visually explained
📂 Tags: #python #ML
http://t.me/codeprogrammer⭐️
http://t.me/codeprogrammer
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MLP by hand ✍️ Excel
📂 Tags: #python #ML #MLP
http://t.me/codeprogrammer⭐️
Download Excel file👇
https://t.me/+Tdshx2j5cZ00N2Ji
http://t.me/codeprogrammer
Download Excel file
https://t.me/+Tdshx2j5cZ00N2Ji
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LeakyReLU by hand ✍️ Excel
📂 Tags: #python #ML #AI
http://t.me/codeprogrammer⭐️
Download Excel file👇
https://t.me/+Tdshx2j5cZ00N2Ji
http://t.me/codeprogrammer
Download Excel file
https://t.me/+Tdshx2j5cZ00N2Ji
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ResNet by hand ✍️ Excel
📂 Tags: #python #ML #AI
http://t.me/codeprogrammer⭐️
Download Excel file👇
https://t.me/+Tdshx2j5cZ00N2Ji
http://t.me/codeprogrammer
Download Excel file
https://t.me/+Tdshx2j5cZ00N2Ji
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Transformer by hand ✍️ Excel
📂 Tags: #python #ML #Transformer
http://t.me/codeprogrammer⭐️
Download Excel file👇
https://t.me/+Tdshx2j5cZ00N2Ji
http://t.me/codeprogrammer
Download Excel file
https://t.me/+Tdshx2j5cZ00N2Ji
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Web scraping will never be the same!
Crawl4AI simplifies web crawling and data extraction, making it ready to use for LLMs and AI applications.
Here’s why it’s a game-changer:
🆓 Free and open-source
⭐️ Blazing fast performance,
🤖 LLM-friendly output formats (JSON, cleaned HTML, markdown)
🌍 Supports crawling multiple URLs simultaneously
🎨 Extracts all media tags (Images, Audio, Video)
🔗 Extracts all external and internal links
But that’s not all:
📚 Extracts metadata from pages
✅ User-agent customization
✅ Takes screenshots of pages
📄 Executes custom JavaScript before crawling
📂 Tags: #python #ML #LLM
http://t.me/codeprogrammer⭐️
Crawl4AI simplifies web crawling and data extraction, making it ready to use for LLMs and AI applications.
Here’s why it’s a game-changer:
But that’s not all:
http://t.me/codeprogrammer
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Transformer by Hand ✍️ in 5 Minutes with Anna Rahn
📂 Tags: #python #ML #Transformer
http://t.me/codeprogrammer⭐️
http://t.me/codeprogrammer
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Pandas ➡️ Polars ➡️ SQL ➡️ PySpark translations:
Is it useful to you❓
📂 Tags: #pandas #Polars #sql #Pyspark
http://t.me/codeprogrammer⭐️
Is it useful to you
http://t.me/codeprogrammer
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Yan Chen - Transformer: Attention by hand ✍️
Is it useful to you❓
📂 Tags: #ML #TRANSFORMER
http://t.me/codeprogrammer⭐️
Is it useful to you
http://t.me/codeprogrammer
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Transformer: Multi-Head Attention
Math vs Code👨💻
I made this visualization to show you how to implement the multi-head attention math in PyTorch within 50 LoC.
Multi-Head Attention is what makes the Transformer's performance outstanding.
Is it useful to you❓
📂 Tags: #ML #TRANSFORMER
http://t.me/codeprogrammer⭐️
Math vs Code
I made this visualization to show you how to implement the multi-head attention math in PyTorch within 50 LoC.
Multi-Head Attention is what makes the Transformer's performance outstanding.
Is it useful to you
http://t.me/codeprogrammer
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