Forwarded from Machine Learning with Python
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Google has published a free guide on scaling AI models and working with GPUs. π
π How to Scale Your Model
https://jax-ml.github.io/scaling-book/
π How to Think About GPUs
https://jax-ml.github.io/scaling-book/gpus/
The materials discuss the principles of model scaling, the structure of GPUs, computational limitations, memory bandwidth, parallelism, and other topics that are useful when training and running modern AI models. π‘
It's completely free and available online. π
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π How to Scale Your Model
https://jax-ml.github.io/scaling-book/
π How to Think About GPUs
https://jax-ml.github.io/scaling-book/gpus/
The materials discuss the principles of model scaling, the structure of GPUs, computational limitations, memory bandwidth, parallelism, and other topics that are useful when training and running modern AI models. π‘
It's completely free and available online. π
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How To Scale Your Model
Training LLMs often feels like alchemy, but understanding and optimizing the performance of your models doesn't have to. This book aims to demystify the science of scaling language models: how TPUs (and GPUs) work and how they communicate with each otherβ¦
β€1
Forwarded from Machine Learning with Python
10 GitHub repositories that are worth checking out for an AI engineer π€
1. Hands-On AI Engineering π οΈ
A collection of AI applications and agent systems with practical use cases of LLM.
π https://github.com/Sumanth077/Hands-On-AI-Engineering
2. Hands-On Large Language Models π
Full code from the book Hands-On Large Language Models: from basics to fine-tuning.
π https://github.com/HandsOnLLM/Hands-On-Large-Language-Models
3. AI Agents for Beginners π
A free course from Microsoft with 11 lessons on creating AI agents.
π https://github.com/microsoft/ai-agents-for-beginners
4. GenAI Agents π€
A large collection of tutorials and implementations of agent systems.
π https://github.com/NirDiamant/GenAI_Agents
5. Made With ML π
About the development, deployment, and support of production-ready ML systems.
π https://github.com/GokuMohandas/Made-With-ML
6. Learn Harness Engineering βοΈ
A practical course on Harness Engineering for AI agents.
π https://github.com/walkinglabs/learn-harness-engineering
7. AutoResearch π¬
Autonomous cycles of ML experiments from Andrej Karpathy.
π https://github.com/karpathy/autoresearch
8. Designing Machine Learning Systems π
Notes and materials from Chip Huyen's book.
π https://github.com/chiphuyen/dmls-book
9. Awesome LLM Inference β‘
A collection of materials on LLM inference: Flash Attention, KV Cache, quantization, and more.
π https://github.com/xlite-dev/Awesome-LLM-Inference
10. LLM Course πΊοΈ
A practical course on LLM with a roadmap and Colab notebooks.
π https://github.com/mlabonne/llm-course
#AI #MachineLearning #LLM #DataScience #Tech #GitHub
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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
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
1. Hands-On AI Engineering π οΈ
A collection of AI applications and agent systems with practical use cases of LLM.
π https://github.com/Sumanth077/Hands-On-AI-Engineering
2. Hands-On Large Language Models π
Full code from the book Hands-On Large Language Models: from basics to fine-tuning.
π https://github.com/HandsOnLLM/Hands-On-Large-Language-Models
3. AI Agents for Beginners π
A free course from Microsoft with 11 lessons on creating AI agents.
π https://github.com/microsoft/ai-agents-for-beginners
4. GenAI Agents π€
A large collection of tutorials and implementations of agent systems.
π https://github.com/NirDiamant/GenAI_Agents
5. Made With ML π
About the development, deployment, and support of production-ready ML systems.
π https://github.com/GokuMohandas/Made-With-ML
6. Learn Harness Engineering βοΈ
A practical course on Harness Engineering for AI agents.
π https://github.com/walkinglabs/learn-harness-engineering
7. AutoResearch π¬
Autonomous cycles of ML experiments from Andrej Karpathy.
π https://github.com/karpathy/autoresearch
8. Designing Machine Learning Systems π
Notes and materials from Chip Huyen's book.
π https://github.com/chiphuyen/dmls-book
9. Awesome LLM Inference β‘
A collection of materials on LLM inference: Flash Attention, KV Cache, quantization, and more.
π https://github.com/xlite-dev/Awesome-LLM-Inference
10. LLM Course πΊοΈ
A practical course on LLM with a roadmap and Colab notebooks.
π https://github.com/mlabonne/llm-course
#AI #MachineLearning #LLM #DataScience #Tech #GitHub
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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
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
Forwarded from Machine Learning with Python
Learn AI for free directly from top companies. π
1 - Anthropic:
anthropic.skilljar.com
2 - Google:
grow.google/ai
3 - Meta:
ai.meta.com/resources/
4 - NVIDIA:
developer.nvidia.com/cuda
5 - Microsoft:
learn.microsoft.com/en-us/training/
6 - OpenAI:
academy.openai.com
7 - IBM:
skillsbuild.org
8 - AWS:
skillbuilder.aws
9 - DeepLearning.AI:
deeplearning.ai
10 - Hugging Face:
huggingface.co/learn
π¬ Comment "Learning" if you find this helpful.
π Repost so others can take help.
π Must bookmark for future reference.
#AI #MachineLearning #Tech #FreeLearning #DataScience #AIForAll
https://xn--r1a.website/CodeProgrammer
1 - Anthropic:
anthropic.skilljar.com
2 - Google:
grow.google/ai
3 - Meta:
ai.meta.com/resources/
4 - NVIDIA:
developer.nvidia.com/cuda
5 - Microsoft:
learn.microsoft.com/en-us/training/
6 - OpenAI:
academy.openai.com
7 - IBM:
skillsbuild.org
8 - AWS:
skillbuilder.aws
9 - DeepLearning.AI:
deeplearning.ai
10 - Hugging Face:
huggingface.co/learn
π¬ Comment "Learning" if you find this helpful.
π Repost so others can take help.
π Must bookmark for future reference.
#AI #MachineLearning #Tech #FreeLearning #DataScience #AIForAll
https://xn--r1a.website/CodeProgrammer
Grow with Google US
AI Training to Grow Your Career | Google
Learn all about AI & how to supercharge your work or business. We offer AI courses and tools that will help you build essential AI skills.
β€4
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π Building our own GPT-like model in PyTorch
We've found an excellent repository for those who want to understand how modern LLMs are built under the hood.
Inside β 10 Jupyter notebooks with step-by-step explanations and implementations of key components of language models.
GitHub: https://github.com/analyticalrohit/llms-from-scratch
#PyTorch #LLM #MachineLearning #AI #DeepLearning #DataScience
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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
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
We've found an excellent repository for those who want to understand how modern LLMs are built under the hood.
Inside β 10 Jupyter notebooks with step-by-step explanations and implementations of key components of language models.
GitHub: https://github.com/analyticalrohit/llms-from-scratch
#PyTorch #LLM #MachineLearning #AI #DeepLearning #DataScience
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
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
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
β€3
Curates LLM tools and research for scientific discovery π§¬π¬
Repo: https://github.com/HKUST-KnowComp/Awesome-LLM-Scientific-Discovery ππ
#LLM #ScientificDiscovery #ResearchTools #AI #MachineLearning #DataScience
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
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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
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
Repo: https://github.com/HKUST-KnowComp/Awesome-LLM-Scientific-Discovery ππ
#LLM #ScientificDiscovery #ResearchTools #AI #MachineLearning #DataScience
β¨ Join Best TG Channels https://xn--r1a.website/addlist/0f6vfFbEMdAwODBk
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
π― One access, lifetime updates
π Use code: PRESALE-BOOK-WAVE-2GFG
π https://helloencyclo.com/?ref=HUSSEINSHEIKHO
β€1
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Attention Heatmap vs Token Pruning πβοΈ
π More: https://www.overshoot.ai/blogs/an-introduction-to-token-pruning-for-vlms
#AI #MachineLearning #TokenPruning #DeepLearning #TechNews #VLM
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π More: https://www.overshoot.ai/blogs/an-introduction-to-token-pruning-for-vlms
#AI #MachineLearning #TokenPruning #DeepLearning #TechNews #VLM
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π Instructions for AI Agents
Please refer to AGENTS.md β a guide dedicated to the file of the same name, which contains instructions for AI agents. π€
The website explains what should be included in AGENTS.md, how to format it correctly, and provides examples from over 60,000 projects. π
http://AGENTS.md/
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#AI #Agents #AGENTSmd #Tech #Development #Programming
Please refer to AGENTS.md β a guide dedicated to the file of the same name, which contains instructions for AI agents. π€
The website explains what should be included in AGENTS.md, how to format it correctly, and provides examples from over 60,000 projects. π
http://AGENTS.md/
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β€3