This media is not supported in your browser
VIEW IN TELEGRAM
Someone spent several months manually writing a 200-page guide on mathematics and the basics of machine learning. π
No marketing fluff or endless links between articles. Just an attempt to gather all the most important things in one place. π―
Inside:
β’ neural networks: backpropagation, SGD, Adam, BatchNorm; βοΈ
β’ classic ML: SVM, Gradient Boosting, K-Means, PCA; π
β’ hardware for AI: Tensor Cores, Systolic Arrays, CUDA; π₯οΈ
β’ transformers: Multi-Head Attention, KV Cache, LoRA; π§
β’ computer vision: ViT, CNN, MAE, IoU, NMS, VLM; ποΈ
β’ agent systems: ReAct, memory, orchestration, OpenClaw. π€
The author describes it as the material he would have wanted to receive himself several years ago. π°οΈ
And yes, the entire guide is distributed free of charge. π
https://www.arjunvirk.com/writing/ml-guide
#MachineLearning #AI #DeepLearning #DataScience #NeuralNetworks #Tech
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
No marketing fluff or endless links between articles. Just an attempt to gather all the most important things in one place. π―
Inside:
β’ neural networks: backpropagation, SGD, Adam, BatchNorm; βοΈ
β’ classic ML: SVM, Gradient Boosting, K-Means, PCA; π
β’ hardware for AI: Tensor Cores, Systolic Arrays, CUDA; π₯οΈ
β’ transformers: Multi-Head Attention, KV Cache, LoRA; π§
β’ computer vision: ViT, CNN, MAE, IoU, NMS, VLM; ποΈ
β’ agent systems: ReAct, memory, orchestration, OpenClaw. π€
The author describes it as the material he would have wanted to receive himself several years ago. π°οΈ
And yes, the entire guide is distributed free of charge. π
https://www.arjunvirk.com/writing/ml-guide
#MachineLearning #AI #DeepLearning #DataScience #NeuralNetworks #Tech
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
π A large collection of AI projects for practice
We found a repository that will help you move from theory to real development of AI applications.
Inside are dozens of ready-made projects: AI analytics, RAG systems, OCR applications, code review agents, travel assistants, and much more.
βοΈ Link to GitHub: https://github.com/Sumanth077/Hands-On-AI-Engineering
#AI #MachineLearning #Python #DataScience #OpenSource #Tech
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
We found a repository that will help you move from theory to real development of AI applications.
Inside are dozens of ready-made projects: AI analytics, RAG systems, OCR applications, code review agents, travel assistants, and much more.
βοΈ Link to GitHub: https://github.com/Sumanth077/Hands-On-AI-Engineering
#AI #MachineLearning #Python #DataScience #OpenSource #Tech
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€5
Multi-Label Text Classification with Scikit-LLM π
In this article, you will learn how to perform multi-label text classification using large language models and the scikit-LLM library, without the need for labeled training data or complex model training. π
Topics we will cover include:
What multi-label classification is and why it matters for nuanced text analysis. π
How to set up and configure scikit-LLM with a free, open-source LLM from Groq for zero-shot inference. βοΈ
How to load a real-world dataset and run multi-label sentiment predictions using a familiar scikit-learn-style workflow. π
Read: https://machinelearningmastery.com/multi-label-text-classification-with-scikit-llm/ π
#ScikitLLM #TextClassification #LLM #MachineLearning #ZeroShot #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
In this article, you will learn how to perform multi-label text classification using large language models and the scikit-LLM library, without the need for labeled training data or complex model training. π
Topics we will cover include:
What multi-label classification is and why it matters for nuanced text analysis. π
How to set up and configure scikit-LLM with a free, open-source LLM from Groq for zero-shot inference. βοΈ
How to load a real-world dataset and run multi-label sentiment predictions using a familiar scikit-learn-style workflow. π
Read: https://machinelearningmastery.com/multi-label-text-classification-with-scikit-llm/ π
#ScikitLLM #TextClassification #LLM #MachineLearning #ZeroShot #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€2
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
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
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
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€4
Classical machine learning equations and diagrams cheat sheet π
https://github.com/soulmachine/machine-learning-cheat-sheet
#MachineLearning #ML #DataScience #CheatSheet #AI #DeepLearning
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
https://github.com/soulmachine/machine-learning-cheat-sheet
#MachineLearning #ML #DataScience #CheatSheet #AI #DeepLearning
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