awesome-data-centric-ai
Awesome-CloudOps-Automation
awesome-data-centric-ai | Awesome-CloudOps-Automation | |
---|---|---|
7 | 15 | |
303 | 283 | |
1.3% | 2.1% | |
3.2 | 9.4 | |
5 months ago | 7 days ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
awesome-data-centric-ai
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Thoughts: Continue current degree with one year left, or start anew with degree apprenticeship
I would finish the degree anyway. It's only one year left. If teachers miss classes, I would disregard that and try to learn on my own, and then yes, I would move on to an internship (or even do It at the same time if it's possible). If you like, come as meet us at the Data-Centric AI Community and we can do some projects together :)
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Data science projects
Definitely a lot of growth in the AI space, and it will evolve rapidly in the next few years. There several paid propositions at the Data-Centric AI Community discord, check them out.
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I absolutely hate my internship
2: Tbh, quit (?) We have open jobs at the Data-Centric AI Community. Bonus points: you can vent there as much as you want
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Prioritise Data Science Projects
Let me invite you to the Data-Centric AI Community we have several code along sessions and projects and a lot of beginners that are starting to learn DS that you can connect with.
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Imbalanced data
If you need specific help with your project you can find me at the Data-Centric AI Community and we'll be happy to take a look and give you some tips to move forward :)
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Building my first Porfolio
You can share with us your progress on the Data-Centric AI Community and ask someone to review it, we often do that with CVs as well and help each other out.
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[Q] How to generate synthetic dataset for anomaly detection?
Maybe you can use a synthetic data generator and use your current dataset as input? I believe there are a lot of GAN-based models for this purpose out there. The ones listed on https://github.com/Data-Centric-AI-Community/awesome-data-centric-ai are mostly focused on structured data, but I'm sure there are similar packages for images.
Awesome-CloudOps-Automation
- Show HN: KRS – K8s runtime health scan utility
- Show HN: UnSkript – Generate SRE Runbooks Using ChatGPT and Jupyter Notebooks
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Show HN: Open-Source, AI Powered Notebooks for SRE Teams
It's a good thing they called themselves "CloudOps" and not "DevOps" because I struggle to think of any sane reason to write code like this
https://github.com/unskript/Awesome-CloudOps-Automation/blob...
(setting aside the lack of try:finally: to close those cursors or why one needs a commit for a SELECT statement)
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Onboarding juniors in a project with complex tech-stack environment
Runbooks implemented using a Jupyter notebook create the perfect way of sharing documentation and scripts in the same place. There is an open source project that you could look into : https://github.com/unskript/Awesome-CloudOps-Automation
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Jupyter Notebooks
Check out unSkript - We are building a platform for runbook automation built on top of Jupyter Notebooks. We have a SAAS version, but all of our RunBooks & Actions are open source: Awesome-CloudOps-Automation (we appreciate stars, and we **love** contributions.)
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Welcome to the unSkript Community
Try them out using our Open source docker container
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What do you use when searching for a SME? A doc, database, app, local notes or something else?
We are building a library of open source runbooks that anyone can use and configure for their environment: https://github.com/unskript/Awesome-CloudOps-Automation
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How to prevent Christmas Cheer from overpowering you
A really cool project about automating the mundane using a notebook approach! I loved the use case they highlighted here in the blog :-) (no office Mariah!)
The open source project is here: https://github.com/unskript/Awesome-CloudOps-Automation
- Show HN: CloudOps Automation Project
- CloudOps Automation Project
What are some alternatives?
ydata-synthetic - Synthetic data generators for tabular and time-series data
awesome-notebooks - A powerful data & AI notebook templates catalog: prompts, plugins, models, workflow automation, analytics, code snippets - following the IMO framework to be searchable and reusable in any context.
machine_learning_complete - A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.
awesome-arr - A collection of *arrs and related stuff.
walkalongs - Resources and solutions of various technologies that I am currently learning
Gauntlet - 🔖 Guides, Articles, Podcasts, Videos and Notes to Build Reliable Large-Scale Distributed Systems.
DataScienceProjects
howtheyaws - A curated collection of publicly available resources on how technology and tech-savvy organizations around the world use Amazon Web Services (AWS)
Portfolio
Awesome-CloudOps-Automaation
fullnamematchscore-go - Generates a match score of two person names from 0-100, where 100 is the highest, on how closely two individual full names match. The scoring is based on a series of tests, algorithms, AI, and an ever-growing body of Machine Learning-based generated knowledge
awesome-sre - A curated list of Site Reliability and Production Engineering resources.