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* ⭐ **[CubeDesk](https://cubedesk.io/)** or **[csTimer](https://cstimer.net/)** - Feature-Rich Cubing Timers
* ⭐ **[SpeedCubeDB](https://speedcubedb.com/)** - Algorithm Database
* [Rubiks Cube Guide](https://rentry.co/cubingguide) - ⁠Guide to Rubiks Cube
* [⁠crystalcube](https://crystalcuber.com/) - CFOP Cross Trainer / Edge Orientation Trainer
* [⁠ZZ Method](https://www.zzmethod.com/) - Learn / Practice ZZ 3x3 Rubiks Speedrunning Method
* [SpeedSolving](https://www.speedsolving.com/) / [Wiki](https://www.speedsolving.com/wiki) or [Ruwix](https://ruwix.com/) - Cubing Wiki / Community Forum
* [World Cube Association](https://www.worldcubeassociation.org/) - Cubing Competitions & Records
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* [systemd-by-example](https://systemd-by-example.com/) - systemd Learning
* [The Linux Kernel](https://www.kernel.org/doc/html/latest/) - Linux Kernel Development Guides / [Archives](https://kernel.org/)
* [Workbench](https://apps.gnome.org/Workbench) - Learn / Experiment with Gnome / [GitHub](https://github.com/workbenchdev/Workbench)
* [⁠aman.ai](https://aman.ai/) - Artificial Intelligence / Deep Learning Stanford Notes
* [LLM Visualization](https://bbycroft.net/llm), [Machine Learning Roadmap](https://rentry.org/machine-learning-roadmap), [SAAYN](https://spreadsheets-are-all-you-need.ai/), [machine-learning-zoomcamp](https://github.com/DataTalksClub/machine-learning-zoomcamp), [ML Engineering](https://github.com/stas00/ml-engineering), [udlbook](https://udlbook.github.io/udlbook/) / [GitHub](https://github.com/udlbook/udlbook/), [mlsysbook](https://www.mlsysbook.ai/), [ML Visualized](https://ml-visualized.com/) / [GitHub](https://github.com/gavinkhung/machine-learning-visualized) or [LLM Course](https://github.com/mlabonne/llm-course) - Learn Machine Learning
* [⁠Transformer Explainer](https://poloclub.github.io/transformer-explainer/) - ⁠Transformer Visuzliation
* [Approaching (Almost) Any Machine Learning Problem](https://files.catbox.moe/b34jd4.pdf) - Machine Learning Problem-Solving Book
* [Deep ML](https://www.deep-ml.com/) - Solve Machine Learning Problems
* [AI-For-Beginners](https://github.com/microsoft/AI-For-Beginners), [Beginner Guides](https://microsoft.github.io/generative-ai-for-beginners/) or [HF Learn](https://huggingface.co/learn) - Machine Learning Guides
* [ML Course Notes](https://github.com/dair-ai/ML-Course-Notes) - Machine Learning Course Notes
* [100-Days-Of-ML-Code](https://github.com/Avik-Jain/100-Days-Of-ML-Code), [DeepLearningWizard](https://www.deeplearningwizard.com/), [DeepCourse](https://arthurdouillard.com/deepcourse/), [UFLDL](http://ufldl.stanford.edu/tutorial/), [IAILab](https://iailab.kaist.ac.kr/teaching/deep-learning), [Handson ML3](https://github.com/ageron/handson-ml3), [DeepLearning.ai](https://www.deeplearning.ai/) or [Practical Deep Learning](https://course.fast.ai/) - Machine / Deep Learning Courses
* [minitorch](https://github.com/minitorch/minitorch) - Machine Learning Engineering Course Code
* [ML YouTube Courses](https://github.com/dair-ai/ML-YouTube-Courses) or [Deep Learning Drizzle](https://deep-learning-drizzle.github.io/) - Machine Learning Courses on YouTube
***
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* 🌐 **[Awesome DataScience](https://github.com/academic/awesome-datascience)** - Data Science Resources
* 🌐 **[Data Engineer Handbook](https://github.com/DataExpert-io/data-engineer-handbook)** - Data Engineer Resources
* ↪️ **[Machine Learning Resources](https://www.reddit.com/r/FREEMEDIAHECKYEAH/wiki/dev-tools/#wiki_.25B7_machine_learning)**
* ↪️ **[Machine / Deep Learning](https://www.reddit.com/r/FREEMEDIAHECKYEAH/wiki/ai#wiki_.25BA_machine_learning)**
* ⭐ **[Open Source Society University](https://github.com/ossu/data-science)** - Data Science Roadmap / [Discord](https://discord.gg/wuytwK5s9h)
* [Mage](https://www.mage.ai/) - Data Science Pipelines
* [Deepnote](https://deepnote.com/) - Data Science Notebook