https://github.com/GabrielSten/awesome

List of stuff on the web I think is worth keeping
https://github.com/GabrielSten/awesome

List: awesome

Last synced: 3 months ago
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List of stuff on the web I think is worth keeping

• Host: GitHub
• URL: https://github.com/GabrielSten/awesome
• Owner: GabrielSten
• Created: 2022-11-21T15:39:29.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2023-09-23T10:21:48.000Z (about 1 year ago)
• Last Synced: 2024-04-11T09:01:42.868Z (7 months ago)
• Size: 40 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• ultimate-awesome - awesome - List of stuff on the web I think is worth keeping. (Other Lists / PowerShell Lists)

README

        
# awesome

List of awesome stuff on the web I think is worth keeping

## Contents

- [Data Science](#Data-Science)

- [Graph Tech](#Graph-Tech)

- [Coding](#Coding)

- [Linux](#Linux)

- [Front End](#Front-End)

- [Distributed Systems](#Distributed-Systems)

- [More Awesome](#More-Awesome)

## Data-Science

- [Educational Implementation of Algorithms in Python](https://github.com/TheAlgorithms/Python)

- [Data Science Resources](https://github.com/jonathan-bower/DataScienceResources)

- [Physics Informed NN](https://benmoseley.blog/my-research/so-what-is-a-physics-informed-neural-network/)

- [Deep Reinforcement Learning](https://github.com/Hadar933/Deep-Reinforcement-Learning)

- [Reinforcement Learning](https://mlu-explain.github.io/reinforcement-learning/)

- [ML visualized](https://mlu-explain.github.io)

- [Aalto Course - Advanced Probablistic Methods](https://fartaha.github.io/ml-advanced-probabilistic-methods/)

- [ChatGPT in 60 lines of NumPy](https://jaykmody.com/blog/gpt-from-scratch/)

- [Free book on deeplearning](https://www.deeplearningbook.org/)

- [Book on ML with PyTorch](https://sebastianraschka.com/blog/2022/ml-pytorch-book.html)

- [DS awesome](https://github.com/Developer-Y/cs-video-courses)

- [Computer Vision Roboflow](https://github.com/roboflow/notebooks)

- [Graph Representation Learning](https://www.cs.mcgill.ca/~wlh/grl_book/files/GRL_Book.pdf)

## Graph-Tech

- [TypeDB with PyTorch](https://blog.vaticle.com/link-prediction-knowledge-graph-pytorch-geometric-f35917320806)

- [ML inspiration for Graphs](https://blog.vaticle.com/unsolved-machine-learning-problems-that-you-can-solve-35e4ddc561b9)

- [20 Graph Algos and Example Uses](https://memgraph.com/blog/graph-algorithms-applications#toc-12)

## Coding

- [Learn Python 3](https://github.com/jerry-git/learn-python3)

- [Efficient Python Coding](https://github.com/youssefHosni/Efficient-Python-for-Data-Scientists)

- [Book on JavaScript](https://eloquentjavascript.net/)

- [Go roadmap](https://roadmap.sh/golang)

- [go generate types from sql](https://github.com/kyleconroy/sqlc?utm_campaign=awesomego&utm_medium=referral&utm_source=awesomego)

## Linux

- [Proxmox Beginners Guide](https://github.com/vzamora/Proxmox-Cheatsheet)

## Front-End

- [SVGs feather](https://feathericons.com/)

- [SVGs tabler](https://tablericons.com/)

- [SVGs phosphor](https://tablericons.com/)

## Distributed-Systems

- [MIT Distributed Systems course](https://www.youtube.com/playlist?list=PLrw6a1wE39_tb2fErI4-WkMbsvGQk9_UB#distributed)

- [Effective Go](https://go.dev/doc/effective_go)

- [Kubebuilder: Intro to K8](https://book.kubebuilder.io/introduction.html)

- [Go Roadmap](https://roadmap.sh/golang)

- [Backend Roadmap](https://roadmap.sh/golang)

## More-Awesome

- [Sindresorhus's Awesome](https://github.com/sindresorhus/awesome/blob/main/readme.md)

- [Hand Drawn Sketch Tool](https://github.com/excalidraw/excalidraw)

- [The Harvard Guide for a Resume](https://hwpi.harvard.edu/files/ocs/files/hes-resume-cover-letter-guide.pdf)

- [Diagrams in HTML](https://reactflow.dev/docs/examples/overview/)

- [APIs gRPC](https://cloud.google.com/apis/design)