5 Fun Papers That Explain LLMs Clearly πβ¨
Want to understand LLMs better? Start with these five foundational papers that explain how they work. π€
Large language models (LLMs) can feel complicated at first. There are transformers, attention layers, scaling laws, pretraining, instruction tuning, human feedback, retrieval, and many other ideas around them. π§ But the best way to understand large language models is not to start with a huge textbook. A better way is to read a few important papers that each explain one major part of the system. π This article is part of a fun series where we learn by exploring core ideas, practical projects, and the research papers behind modern technology. π¬ In this article, we will go through five papers that explain how LLMs work. So, let's get started. π
More: https://www.kdnuggets.com/5-fun-papers-that-explain-llms-clearly
#LLM #AI #MachineLearning #DeepLearning #DataScience #Tech
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Want to understand LLMs better? Start with these five foundational papers that explain how they work. π€
Large language models (LLMs) can feel complicated at first. There are transformers, attention layers, scaling laws, pretraining, instruction tuning, human feedback, retrieval, and many other ideas around them. π§ But the best way to understand large language models is not to start with a huge textbook. A better way is to read a few important papers that each explain one major part of the system. π This article is part of a fun series where we learn by exploring core ideas, practical projects, and the research papers behind modern technology. π¬ In this article, we will go through five papers that explain how LLMs work. So, let's get started. π
More: https://www.kdnuggets.com/5-fun-papers-that-explain-llms-clearly
#LLM #AI #MachineLearning #DeepLearning #DataScience #Tech
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
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β€5
GRU β remembers efficiently
GAN β creates realistic content
RNN β understands sequences
LSTM β remembers long context
https://t.me/CodeProgrammer
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β€5π2π₯1
Forwarded from Machine Learning
If you already have 200 open tabs with courses, articles, and GitHub repositories on ML, this repository might save the situation a bit. π
Awesome Machine Learning Resources is a huge collection of sub-collections on machine learning, deep learning, and AI. π€
Instead of endless Google searches, everything is organized into categories:
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β’ neural networks and modern architectures
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Each link has a short description, so you can quickly understand whether it's worth opening it or skipping it. π
I particularly liked that the authors mark abandoned collections with an icon if they haven't been updated in over a year. β οΈ
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
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π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
Awesome Machine Learning Resources is a huge collection of sub-collections on machine learning, deep learning, and AI. π€
Instead of endless Google searches, everything is organized into categories:
β’ fundamentals of machine learning
β’ neural networks and modern architectures
β’ tasks and application areas
β’ datasets
β’ libraries and tools
β’ fairness and AI ethics
β’ production ML and MLOps
Each link has a short description, so you can quickly understand whether it's worth opening it or skipping it. π
I particularly liked that the authors mark abandoned collections with an icon if they haven't been updated in over a year. β οΈ
https://github.com/ZhiningLiu1998/awesome-machine-learning-resources
#MachineLearning #DeepLearning #AI #MLOps #DataScience #TechResources
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βοΈ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
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π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
β€4
Forwarded from Vinayak Chiluka
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At HelloEncyclo, we're building a comprehensive AI-powered learning platform designed to help students, professionals, and career switchers gain practical, industry-relevant skills through structured learning paths.
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π’ Stay updated with new course launches, discounts, learning resources, interview preparation tips, and career guidance:
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Don't want to read about AI Engineering, but actually want to build something? π οΈ
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Everything is free, with source code and ready-made examples. π₯©
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
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π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
We've released a collection of 50+ practical tutorials on AI Engineering as open source. π
Inside, you'll find step-by-step projects on:
β’ AI agents and multi-agent systems π€
β’ RAG (Agentic, Vision, and Local) π
β’ MCP agents βοΈ
β’ OCR applications π
β’ Voice AI agents ποΈ
β’ and much more β¨
Everything is free, with source code and ready-made examples. π₯©
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GitHub
GitHub - Sumanth077/Hands-On-AI-Engineering: A curated collection of practical AI projects implementing OCR systems, RAG, AI agentsβ¦
A curated collection of practical AI projects implementing OCR systems, RAG, AI agents, and other AI use cases. - Sumanth077/Hands-On-AI-Engineering
β€4π2
Agentic_Design_Patterns.pdf
19.2 MB
Agentic Design Patterns - a free 421-page document from a senior Google engineer. πβ¨
It's rare to find materials of such a large volume where the author doesn't try to sell a course after every chapter. π‘
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It's rare to find materials of such a large volume where the author doesn't try to sell a course after every chapter. π‘
Inside:
⬩ agent architectures
⬩ multi-agent systems
⬩ memory and context management
⬩ orchestration and task planning
⬩ tools, MCP, and integrations
⬩ production cases and code examples
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
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π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
Over five days, they will explain how agent-based coding works, how to configure skills, memory, and context, and how to make AI assistants not only useful but also safe. π€ The program includes daily tasks, live streams, discussions, and practical projects. π»
After completion, participants will receive an official certificate that can be added to their portfolio. π
Start date: June 15th. π
https://www.kaggle.com/competitions/5-day-ai-agents-intensive-vibecoding-course-with-google π
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
β 13 courses live + 40+ coming soon
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A comprehensive Python training course that systematically covers the basics of the language: variables, conditions, loops, functions, lists, dictionaries, OOP, etc. The material is accompanied by code examples and clear explanations, making it suitable even for those who are just starting their journey in programming.
π I'll leave a link: beginnersbook.com
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π Level up your AI & Data Science skills with HelloEncyclo β a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
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π https://helloencyclo.com/?ref=HUSSEINSHEIKHO