Forwarded from Data Analytics
One of the key moments when I truly understood how transformers work: 🧠✨
"Stop thinking of a transformer as a conveyor belt, where each layer transforms the output of the previous one."
"Start thinking of it as a residual flow." 🌊
Each block in a transformer has a residual connection that adds the input of the block to its output:
Because of this addition, the attention mechanism or MLP within the layer – the function f in the formula above – actually does NOT transform the input. Instead, it calculates the information that needs to be ADDED to the input before passing it to the next block! ➕
Imagine the main part of the transformer as a shared whiteboard. 📝 Each block reads what it needs from it and adds its own notes. All changes are additions.
Furthermore, layers can exchange information over distances. A block in the first layer can write information, and a block in the fifth layer can read it, even though there is no direct connection between them. 🔗
I owe these ideas to an older article by Anthropic about the architecture of transformers:
transformer-circuits.pub/2021/framework
#Transformers #DeepLearning #AI #MachineLearning #NeuralNetworks #Tech
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"Stop thinking of a transformer as a conveyor belt, where each layer transforms the output of the previous one."
"Start thinking of it as a residual flow." 🌊
Each block in a transformer has a residual connection that adds the input of the block to its output:
x' = f(x) + x
Because of this addition, the attention mechanism or MLP within the layer – the function f in the formula above – actually does NOT transform the input. Instead, it calculates the information that needs to be ADDED to the input before passing it to the next block! ➕
Imagine the main part of the transformer as a shared whiteboard. 📝 Each block reads what it needs from it and adds its own notes. All changes are additions.
Furthermore, layers can exchange information over distances. A block in the first layer can write information, and a block in the fifth layer can read it, even though there is no direct connection between them. 🔗
I owe these ideas to an older article by Anthropic about the architecture of transformers:
transformer-circuits.pub/2021/framework
#Transformers #DeepLearning #AI #MachineLearning #NeuralNetworks #Tech
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❤8👍1
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2. The Big Book of Small Python Projects
https://inventwithpython.com/bigbookpython/
3. Data Structures
https://opendatastructures.org/ods-python.pdf
4. Data Science Handbook
https://t.co/9aOLdiAbim
5. Data Analysis
https://wesmckinney.com/book/
6. Data Science
https://t.co/TusyBWGfrx
7. Machine Learning
https://t.co/7veOwESe8q
8. Statistics
https://t.co/waWDQylQpY
9. Think Bayes
https://allendowney.github.io/ThinkBayes2/
10. Clean Code in Python — Packt
https://t.co/OHhVgF1L65
#Python #FreeBooks #Programming #DataScience #MachineLearning #Coding
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1. Think Python — O’Reilly
https://t.co/X7y3pX68IW
2. The Big Book of Small Python Projects
https://inventwithpython.com/bigbookpython/
3. Data Structures
https://opendatastructures.org/ods-python.pdf
4. Data Science Handbook
https://t.co/9aOLdiAbim
5. Data Analysis
https://wesmckinney.com/book/
6. Data Science
https://t.co/TusyBWGfrx
7. Machine Learning
https://t.co/7veOwESe8q
8. Statistics
https://t.co/waWDQylQpY
9. Think Bayes
https://allendowney.github.io/ThinkBayes2/
10. Clean Code in Python — Packt
https://t.co/OHhVgF1L65
#Python #FreeBooks #Programming #DataScience #MachineLearning #Coding
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⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
❤7
"Graph Theory with Applications" is a free textbook that provides a comprehensive introduction to graph theory and its practical applications.
The book begins with basic concepts: graphs, subgraphs, paths, cycles, trees, and connectivity. It then moves on to more advanced topics: Eulerian and Hamiltonian graphs, matching, graph coloring, planar and directed graphs, network flows, and extremal graph theory.
What is particularly useful is that the authors combine a visual, geometric, and topological understanding of graphs with a rigorous presentation of the mathematical foundations.
This makes the book a valuable resource for studying the theory that underlies many modern applications of graphs in computer science, computer networks, optimization, data analysis, and related fields.
Book: https://book.huihoo.com/pdf/graph-theory-with-applications.pdf
https://t.me/CodeProgrammer
The book begins with basic concepts: graphs, subgraphs, paths, cycles, trees, and connectivity. It then moves on to more advanced topics: Eulerian and Hamiltonian graphs, matching, graph coloring, planar and directed graphs, network flows, and extremal graph theory.
What is particularly useful is that the authors combine a visual, geometric, and topological understanding of graphs with a rigorous presentation of the mathematical foundations.
This makes the book a valuable resource for studying the theory that underlies many modern applications of graphs in computer science, computer networks, optimization, data analysis, and related fields.
Book: https://book.huihoo.com/pdf/graph-theory-with-applications.pdf
https://t.me/CodeProgrammer
❤7
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Are you a researcher, student, business owner, or developer looking for professional support? We are here to help you turn your ideas into real results! 💡
🔬 1. Scientific Research & Academic Publishing
Professional review and evaluation of scientific manuscripts before submission.
Guidance on journal selection and publication strategies.
Expert advice to improve research quality and presentation.
Support for researchers throughout the academic publishing process.
💻 2. Website & Software Development
Professional website design and development for businesses and individuals.
Custom electronic systems tailored to your needs.
Technical assistance for students and academic projects.
⚙️ 3. API & User Interface (UI) Services
API development and integration.
Modern, responsive, and user-friendly interface design.
Seamless integration between applications and systems.
📊 4. Real-World & Synthetic Datasets
Providing real-world datasets for research and analysis.
Creating customized synthetic datasets according to your requirements.
Data support for scientific research, machine learning, and AI projects.
🤝 5. FREE Discussion & Consultation
Discuss your research ideas and technical projects with us.
Get initial guidance and recommendations.
Explore the best solutions for your academic or professional needs.
🌟 WHY CHOOSE US?
✅ Research and technology expertise in one place.
✅ Tailored solutions based on your needs.
✅ Professional guidance and practical support.
✅ Free initial discussion and consultation.
📩 CONTACT US ON TELEGRAM
👨💻 Team Admin & Support: @Omidyzd62
💬 Feel free to contact us to discuss your ideas, ask questions, or explore how we can help!
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❤4👍1💯1
Forwarded from Machine Learning
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✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
The platform offers:
🫡 1200+ machine learning tasks;
🫡 Mathematics, from linear algebra to PCA;
🫡 Deep Learning, NLP, and Computer Vision;
🫡 Labs with real datasets;
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🫡 Projects using GPT, RL, and CUDA.
Almost everything can be accessed directly in your browser, and basic tasks are available for free.
⛓️ Link to the platform
https://enghusseinsheikho.substack.com/p/a-comprehensive-resource-for-machine?r=3hwnr8&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true
#MachineLearning #DeepLearning #DataScience #AI #Coding #Tech
✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
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https://substack.com/@husseinsheikho?utm_source=share&utm_medium=android&r=3hwnr8
Follow me to more posts and useful content
Follow me to more posts and useful content
Substack
Hussein Sheikho | Substack
AI and Machine Learning Blogger | Computer Vision & Image Processing | Python Developer. Sharing practical tutorials, innovative projects, and insights into deep learning and artificial intelligence.
❤2👍1
📚 7 Best Websites to Learn Computer Science Subjects for Free
More: https://enghusseinsheikho.substack.com/p/7-best-websites-to-learn-computer?r=3hwnr8&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true
More: https://enghusseinsheikho.substack.com/p/7-best-websites-to-learn-computer?r=3hwnr8&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true
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Learn Deep Learning Cheat Sheet
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Forwarded from Machine Learning
Agentic AI is the future.
If you want to become god-level with AI agents, save these 10 GitHub repos:
1 Awesome LLM Apps
🔗 https://github.com/Shubhamsaboo/awesome-llm-apps
2 Generative AI for Beginners
🔗 https://github.com/microsoft/generative-ai-for-beginners
3 LLM Course
🔗 https://github.com/mlabonne/llm-course
4 Prompt Engineering Guide
🔗 https://github.com/dair-ai/Prompt-Engineering-Guide
5 AI Agents for Beginners
🔗 https://github.com/microsoft/ai-agents-for-beginners
6 AI Agents Projects
🔗 https://github.com/ashishpatel26/500-AI-Agents-Projects
7 Hugging Face Agents Course
🔗 https://github.com/huggingface/agents-course
8 Awesome AI Agents
🔗 https://github.com/e2b-dev/awesome-ai-agents
9 GenAI Agents
🔗 https://github.com/NirDiamant/GenAI_Agents
10 Agents Towards Production
🔗 https://github.com/NirDiamant/agents-towards-production
Anything else you'd add?
If you want to become god-level with AI agents, save these 10 GitHub repos:
1 Awesome LLM Apps
🔗 https://github.com/Shubhamsaboo/awesome-llm-apps
2 Generative AI for Beginners
🔗 https://github.com/microsoft/generative-ai-for-beginners
3 LLM Course
🔗 https://github.com/mlabonne/llm-course
4 Prompt Engineering Guide
🔗 https://github.com/dair-ai/Prompt-Engineering-Guide
5 AI Agents for Beginners
🔗 https://github.com/microsoft/ai-agents-for-beginners
6 AI Agents Projects
🔗 https://github.com/ashishpatel26/500-AI-Agents-Projects
7 Hugging Face Agents Course
🔗 https://github.com/huggingface/agents-course
8 Awesome AI Agents
🔗 https://github.com/e2b-dev/awesome-ai-agents
9 GenAI Agents
🔗 https://github.com/NirDiamant/GenAI_Agents
10 Agents Towards Production
🔗 https://github.com/NirDiamant/agents-towards-production
Anything else you'd add?
GitHub
GitHub - Shubhamsaboo/awesome-llm-apps: 100+ AI Agents, Agent Skills and RAG Apps - Free and Open Source.
100+ AI Agents, Agent Skills and RAG Apps - Free and Open Source. - Shubhamsaboo/awesome-llm-apps
🔥4❤3
Forwarded from Data Analytics
If you want to get GOAT-level at software engineering,
save & star these 10 GitHub repos:
1 System design academy
↳ https://github.com/systemdesign42/system-design-academy
2 Public APIs
↳ https://github.com/public-apis/public-apis
3 Tech interview handbook
↳ https://github.com/yangshun/tech-interview-handbook
4 Coding interview university
↳ https://github.com/jwasham/coding-interview-university
5 Engineering leadership
↳ https://github.com/gregorojstersek/resources-to-become-a-great-engineering-leader
6 Freecodecamp
↳ https://github.com/freeCodeCamp/freeCodeCamp
7 Developer roadmaps
↳ https://github.com/kamranahmedse/developer-roadmap
8 Path to senior engineer handbook
↳ https://github.com/jordan-cutler/path-to-senior-engineer-handbook
9 Free programming books
↳ https://github.com/EbookFoundation/free-programming-books
10 Build your own x
↳ https://github.com/codecrafters-io/build-your-own-x
Anything else you'd add?
♻ Repost to help others become better engineers.
https://t.me/DataAnalyticsX 🧑🏻💻
save & star these 10 GitHub repos:
1 System design academy
↳ https://github.com/systemdesign42/system-design-academy
2 Public APIs
↳ https://github.com/public-apis/public-apis
3 Tech interview handbook
↳ https://github.com/yangshun/tech-interview-handbook
4 Coding interview university
↳ https://github.com/jwasham/coding-interview-university
5 Engineering leadership
↳ https://github.com/gregorojstersek/resources-to-become-a-great-engineering-leader
6 Freecodecamp
↳ https://github.com/freeCodeCamp/freeCodeCamp
7 Developer roadmaps
↳ https://github.com/kamranahmedse/developer-roadmap
8 Path to senior engineer handbook
↳ https://github.com/jordan-cutler/path-to-senior-engineer-handbook
9 Free programming books
↳ https://github.com/EbookFoundation/free-programming-books
10 Build your own x
↳ https://github.com/codecrafters-io/build-your-own-x
Anything else you'd add?
♻ Repost to help others become better engineers.
https://t.me/DataAnalyticsX 🧑🏻💻
❤4👍2