10 GitHub repositories that are worth checking out for an AI engineer 🤖
1. Hands-On AI Engineering 🛠️
A collection of AI applications and agent systems with practical use cases of LLM.
👉 https://github.com/Sumanth077/Hands-On-AI-Engineering
2. Hands-On Large Language Models 📘
Full code from the book Hands-On Large Language Models: from basics to fine-tuning.
👉 https://github.com/HandsOnLLM/Hands-On-Large-Language-Models
3. AI Agents for Beginners 🎓
A free course from Microsoft with 11 lessons on creating AI agents.
👉 https://github.com/microsoft/ai-agents-for-beginners
4. GenAI Agents 🤖
A large collection of tutorials and implementations of agent systems.
👉 https://github.com/NirDiamant/GenAI_Agents
5. Made With ML 🚀
About the development, deployment, and support of production-ready ML systems.
👉 https://github.com/GokuMohandas/Made-With-ML
6. Learn Harness Engineering ⚙️
A practical course on Harness Engineering for AI agents.
👉 https://github.com/walkinglabs/learn-harness-engineering
7. AutoResearch 🔬
Autonomous cycles of ML experiments from Andrej Karpathy.
👉 https://github.com/karpathy/autoresearch
8. Designing Machine Learning Systems 📚
Notes and materials from Chip Huyen's book.
👉 https://github.com/chiphuyen/dmls-book
9. Awesome LLM Inference ⚡
A collection of materials on LLM inference: Flash Attention, KV Cache, quantization, and more.
👉 https://github.com/xlite-dev/Awesome-LLM-Inference
10. LLM Course 🗺️
A practical course on LLM with a roadmap and Colab notebooks.
👉 https://github.com/mlabonne/llm-course
#AI #MachineLearning #LLM #DataScience #Tech #GitHub
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🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
✅ 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO
1. Hands-On AI Engineering 🛠️
A collection of AI applications and agent systems with practical use cases of LLM.
👉 https://github.com/Sumanth077/Hands-On-AI-Engineering
2. Hands-On Large Language Models 📘
Full code from the book Hands-On Large Language Models: from basics to fine-tuning.
👉 https://github.com/HandsOnLLM/Hands-On-Large-Language-Models
3. AI Agents for Beginners 🎓
A free course from Microsoft with 11 lessons on creating AI agents.
👉 https://github.com/microsoft/ai-agents-for-beginners
4. GenAI Agents 🤖
A large collection of tutorials and implementations of agent systems.
👉 https://github.com/NirDiamant/GenAI_Agents
5. Made With ML 🚀
About the development, deployment, and support of production-ready ML systems.
👉 https://github.com/GokuMohandas/Made-With-ML
6. Learn Harness Engineering ⚙️
A practical course on Harness Engineering for AI agents.
👉 https://github.com/walkinglabs/learn-harness-engineering
7. AutoResearch 🔬
Autonomous cycles of ML experiments from Andrej Karpathy.
👉 https://github.com/karpathy/autoresearch
8. Designing Machine Learning Systems 📚
Notes and materials from Chip Huyen's book.
👉 https://github.com/chiphuyen/dmls-book
9. Awesome LLM Inference ⚡
A collection of materials on LLM inference: Flash Attention, KV Cache, quantization, and more.
👉 https://github.com/xlite-dev/Awesome-LLM-Inference
10. LLM Course 🗺️
A practical course on LLM with a roadmap and Colab notebooks.
👉 https://github.com/mlabonne/llm-course
#AI #MachineLearning #LLM #DataScience #Tech #GitHub
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🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
✅ 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO
❤9👍2
🎓 A Free AI Course for Beginners by Microsoft
For those just getting into artificial intelligence, Microsoft offers a free course.
It runs for 12 weeks and includes 24 lessons with theory, hands-on assignments, labs, and quizzes.
The curriculum covers neural networks and deep learning, computer vision, natural language processing, genetic algorithms, and AI ethics. For practice, it uses the two main ML frameworks—TensorFlow and PyTorch.
Each lesson follows the same structure: first, reading material, then a Jupyter notebook with code, and for some topics, a lab. The course is in English but has been translated into dozens of languages.
➡️ All materials and links are on GitHub
https://github.com/microsoft/AI-For-Beginners/blob/main/translations/ru/README.md
What's your AI level right now?
❤️ — Advanced user
🔥 — Almost zero
#AICourse #Microsoft #DeepLearning #TensorFlow #PyTorch #MachineLearning
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🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
✅ 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO
For those just getting into artificial intelligence, Microsoft offers a free course.
It runs for 12 weeks and includes 24 lessons with theory, hands-on assignments, labs, and quizzes.
The curriculum covers neural networks and deep learning, computer vision, natural language processing, genetic algorithms, and AI ethics. For practice, it uses the two main ML frameworks—TensorFlow and PyTorch.
Each lesson follows the same structure: first, reading material, then a Jupyter notebook with code, and for some topics, a lab. The course is in English but has been translated into dozens of languages.
➡️ All materials and links are on GitHub
https://github.com/microsoft/AI-For-Beginners/blob/main/translations/ru/README.md
What's your AI level right now?
❤️ — Advanced user
🔥 — Almost zero
#AICourse #Microsoft #DeepLearning #TensorFlow #PyTorch #MachineLearning
✨ Join Best TG Channels https://t.iss.one/addlist/0f6vfFbEMdAwODBk
⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
✅ 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO
❤5👍1
Forwarded from Machine Learning
Classical machine learning equations and diagrams cheat sheet 📊
https://github.com/soulmachine/machine-learning-cheat-sheet
#MachineLearning #ML #DataScience #CheatSheet #AI #DeepLearning
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🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
✅ 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO
https://github.com/soulmachine/machine-learning-cheat-sheet
#MachineLearning #ML #DataScience #CheatSheet #AI #DeepLearning
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🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more.
✅ 13 courses live + 40+ coming soon
🎯 One access, lifetime updates
🔑 Use code: PRESALE-BOOK-WAVE-2GFG
👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO
❤7
Learn AI for free directly from top companies. 🚀
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
💬 Comment "Learning" if you find this helpful.
🔄 Repost so others can take help.
🔖 Must bookmark for future reference.
#AI #MachineLearning #Tech #FreeLearning #DataScience #AIForAll
https://t.iss.one/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
💬 Comment "Learning" if you find this helpful.
🔄 Repost so others can take help.
🔖 Must bookmark for future reference.
#AI #MachineLearning #Tech #FreeLearning #DataScience #AIForAll
https://t.iss.one/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.
❤12👍4
Forwarded from Machine Learning
500 AI/ML/Computer Vision/NLP projects with code 🚀
This is a large collection of 500 ready-made projects in the field of machine learning, deep learning, computer vision, and NLP 🧠
All examples come with code, so you can not just read them, but immediately analyze and run them ⚙️
➡️ Link to GitHub:
https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code
#AI #MachineLearning #DeepLearning #ComputerVision #NLP #DataScience
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This is a large collection of 500 ready-made projects in the field of machine learning, deep learning, computer vision, and NLP 🧠
All examples come with code, so you can not just read them, but immediately analyze and run them ⚙️
➡️ Link to GitHub:
https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code
#AI #MachineLearning #DeepLearning #ComputerVision #NLP #DataScience
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❤12
Transformers become more understandable when you can "poke" the model directly. 🧠✨
Transformer Explainer is an interactive visualization tool for studying how text-generating transformer-based models, such as GPT, work. 🔍
It helps connect the architecture with real behavior by running a live GPT-2 directly in the browser, allowing you to enter your own text and showing how the internal components work together to predict the next tokens. 🔄📝
Key features: 🌟
- Live GPT-2 in the browser - experiment without setting up a separate model server 💻
- Your own text - try your own prompts and see how the model processes them ✍️
- Internal components - observe the operations working inside the transformer 🔧
- Focus on predicting the next token - link each visual step to the model's predictions 🎯
- Local development - clone the repository, install dependencies, and run via npm for in-depth study ⚙️
It's open-source (MIT license). 📜
https://github.com/poloclub/transformer-explainer
#AI #MachineLearning #GPT #DataScience #TechTools #OpenSource
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Transformer Explainer is an interactive visualization tool for studying how text-generating transformer-based models, such as GPT, work. 🔍
It helps connect the architecture with real behavior by running a live GPT-2 directly in the browser, allowing you to enter your own text and showing how the internal components work together to predict the next tokens. 🔄📝
Key features: 🌟
- Live GPT-2 in the browser - experiment without setting up a separate model server 💻
- Your own text - try your own prompts and see how the model processes them ✍️
- Internal components - observe the operations working inside the transformer 🔧
- Focus on predicting the next token - link each visual step to the model's predictions 🎯
- Local development - clone the repository, install dependencies, and run via npm for in-depth study ⚙️
It's open-source (MIT license). 📜
https://github.com/poloclub/transformer-explainer
#AI #MachineLearning #GPT #DataScience #TechTools #OpenSource
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❤5
Reinforcement Learning Methods and Tutorials 🧠📚
In these tutorials for reinforcement learning, it covers from the basic RL algorithms to advanced algorithms developed recent years.
Learning Resources: https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow 🚀
Here's a collection of simple materials on methods and practical guides, covering both basic reinforcement learning algorithms and modern, recently developed, and updated advanced algorithms. 📖✨
#ReinforcementLearning #MachineLearning #AI #DeepLearning #TechTutorials #DataScience
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In these tutorials for reinforcement learning, it covers from the basic RL algorithms to advanced algorithms developed recent years.
Learning Resources: https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow 🚀
Here's a collection of simple materials on methods and practical guides, covering both basic reinforcement learning algorithms and modern, recently developed, and updated advanced algorithms. 📖✨
#ReinforcementLearning #MachineLearning #AI #DeepLearning #TechTutorials #DataScience
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❤12
Forwarded from Machine Learning
Diving deep into Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP. 🤖🧠
Lectures: 🎓📚
https://github.com/kmario23/deep-learning-drizzle
#DeepLearning #MachineLearning #AI #ReinforcementLearning #ComputerVision #NLP
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Lectures: 🎓📚
https://github.com/kmario23/deep-learning-drizzle
#DeepLearning #MachineLearning #AI #ReinforcementLearning #ComputerVision #NLP
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❤6👍1💯1
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Hugging Face Viewer is now at 2300 viewable models! 😊 Would love more feedback and ideas!
It's a free interactive graph visualizer for learning about the architectures of open source AI models! 🚀
Hovering nodes in the graph links to a definitions + animation and the paper that introduced it!
🌟 hfviewer.com
#HuggingFace #AI #MachineLearning #OpenSource #TechNews #DataViz
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It's a free interactive graph visualizer for learning about the architectures of open source AI models! 🚀
Hovering nodes in the graph links to a definitions + animation and the paper that introduced it!
🌟 hfviewer.com
#HuggingFace #AI #MachineLearning #OpenSource #TechNews #DataViz
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❤9
🔖 Comprehensive Practical Course on Reinforcement Learning
We've found a repository that will help you learn Reinforcement Learning, from basic concepts to advanced algorithms.
The author supports the theory with practical examples using TensorFlow, making the material ideal for self-study.
⛓️ Link to GitHub
https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow
#ReinforcementLearning #TensorFlow #MachineLearning #DeepLearning #AI #Tech
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We've found a repository that will help you learn Reinforcement Learning, from basic concepts to advanced algorithms.
The author supports the theory with practical examples using TensorFlow, making the material ideal for self-study.
⛓️ Link to GitHub
https://github.com/MorvanZhou/Reinforcement-learning-with-tensorflow
#ReinforcementLearning #TensorFlow #MachineLearning #DeepLearning #AI #Tech
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❤4
Forwarded from Machine Learning
Maths, CS & AI Compendium: A free textbook for aspiring AI/ML engineers
🚀 A large open-source compendium on mathematics, computer science, and AI has gone viral on GitHub. The project already has around 6.3K stars.
📚 The author positions it as a "non-traditional textbook" for practitioners: less dry notation, more intuition, connections between topics, and real-world context.
📖 It contains 20 chapters:
* Vectors, matrices, calculus
* Statistics and probability
* Machine learning and deep learning
* NLP, computer vision, audio/speech
* Multimodal learning and autonomous systems
* GNN, OS, algorithms
* Production engineering, GPU/SIMD
* AI inference, ML systems design, and applied AI
🤖 There is also a MCP server so that Claude Code, Cursor, VS Code, and other AI assistants can use the compendium as a local knowledge base.
💡 This is a great resource for those who want to not just "learn ML," but to build a solid foundation: mathematics → CS → ML systems → modern AI.
🔗 GitHub: https://github.com/HenryNdubuaku/maths-cs-ai-compendium
#AI #MachineLearning #ComputerScience #Maths #OpenSource #DevCommunity
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🚀 A large open-source compendium on mathematics, computer science, and AI has gone viral on GitHub. The project already has around 6.3K stars.
📚 The author positions it as a "non-traditional textbook" for practitioners: less dry notation, more intuition, connections between topics, and real-world context.
📖 It contains 20 chapters:
* Vectors, matrices, calculus
* Statistics and probability
* Machine learning and deep learning
* NLP, computer vision, audio/speech
* Multimodal learning and autonomous systems
* GNN, OS, algorithms
* Production engineering, GPU/SIMD
* AI inference, ML systems design, and applied AI
🤖 There is also a MCP server so that Claude Code, Cursor, VS Code, and other AI assistants can use the compendium as a local knowledge base.
💡 This is a great resource for those who want to not just "learn ML," but to build a solid foundation: mathematics → CS → ML systems → modern AI.
🔗 GitHub: https://github.com/HenryNdubuaku/maths-cs-ai-compendium
#AI #MachineLearning #ComputerScience #Maths #OpenSource #DevCommunity
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❤5
Top YouTube Channels to Master Tech Skills 🚀
1. SQL 💻
👉 youtube.com/@joeyblue1
2. Excel 📊
👉 youtube.com/@excelisfun
3. Statistics 📈
👉 youtube.com/@statquest
4. Math 🧮
👉 youtube.com/results?search…
5. Python 🐍
👉 youtube.com/@BroCodez
6. Data Analysis 🔍
👉 youtube.com/@AlexTheAnalyst
7. Machine Learning 🤖
👉 youtube.com/@campusx-offic…
8. Deep Learning 🧠
👉 youtube.com/@deeplizard
9. Java ☕
👉 youtube.com/@Telusko
10. Big Data 📦
👉 youtube.com/@thedatatech
11. Data Engineering ⚙️
👉 youtube.com/@dataengineeri…
12. NLP (Natural Language Processing) 🗣️
👉 youtube.com/@codebasics
13. Computer Vision & AI 👁️
👉 youtube.com/@murtazasworks…
14. Generative AI ✨
👉 youtube.com/@sunnysavita10
15. University-Level Courses 🎓
👉 youtube.com/@stanfordonline
👉 youtube.com/@mitocw
16. All-in-One Learning 📚
👉 youtube.com/@freecodecamp
#TechSkills #YouTube #DataScience #Programming #MachineLearning #LearnTech
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1. SQL 💻
👉 youtube.com/@joeyblue1
2. Excel 📊
👉 youtube.com/@excelisfun
3. Statistics 📈
👉 youtube.com/@statquest
4. Math 🧮
👉 youtube.com/results?search…
5. Python 🐍
👉 youtube.com/@BroCodez
6. Data Analysis 🔍
👉 youtube.com/@AlexTheAnalyst
7. Machine Learning 🤖
👉 youtube.com/@campusx-offic…
8. Deep Learning 🧠
👉 youtube.com/@deeplizard
9. Java ☕
👉 youtube.com/@Telusko
10. Big Data 📦
👉 youtube.com/@thedatatech
11. Data Engineering ⚙️
👉 youtube.com/@dataengineeri…
12. NLP (Natural Language Processing) 🗣️
👉 youtube.com/@codebasics
13. Computer Vision & AI 👁️
👉 youtube.com/@murtazasworks…
14. Generative AI ✨
👉 youtube.com/@sunnysavita10
15. University-Level Courses 🎓
👉 youtube.com/@stanfordonline
👉 youtube.com/@mitocw
16. All-in-One Learning 📚
👉 youtube.com/@freecodecamp
#TechSkills #YouTube #DataScience #Programming #MachineLearning #LearnTech
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❤6