awesome-data-centric-ai
machine_learning_complete
| awesome-data-centric-ai | machine_learning_complete | |
|---|---|---|
| 7 | 2 | |
| 303 | 4,514 | |
| 1.0% | - | |
| 3.2 | 5.9 | |
| 5 months ago | 8 months ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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.
machine_learning_complete
What are some alternatives?
ydata-synthetic - Synthetic data generators for tabular and time-series data
embedding-encoder - Scikit-Learn compatible transformer that turns categorical variables into dense entity embeddings.
walkalongs - Resources and solutions of various technologies that I am currently learning
CardMap - Code to plot cardmarket orders on a map to show where my MtG cards ended up
DataScienceProjects
event-transcripts - transcripts from our recorded events
Portfolio
PtitPrince - python version of raincloud
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
Andrew-NG-Notes - This is Andrew NG Coursera Handwritten Notes.
awesome-generative-ai-companies - A curated list of GŠµnerative AI companies, sorted by focus area and total fundraised amount.
artificial-intelligence - AI projects in python, mostly Jupyter notebooks.