A list of 99 machine learning projects for anyone interested to learn machine learning from coding and building projects.
This is still work-in-progress, but I hope that people can start contributing codes. For now, I'm going with the 'create whatever and we will sort out later' approach. Feel free to create issues to propose ideas, questions, comments and complaints.
The format is roughly the following:
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Propose an exercise by creating an issue ticket and write what you think is an useful coding exercise for certain concepts.
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If enough people are interested in that issue ticket, hopefully either you or someone else will write the exercise statement properly similar to the style of a lab exercise/homework question.
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Then someone will fork the repo, write up their solution, with a bit of polish and documentation, submit a pull request. I'm going to write up a contributing guide soon. For now, the guideline is just: create a folder, say '001' with two subfolder 'exercise' and 'solution. Then dump codes inside. I created a silly project 000 as an example of a hello-world Python code.
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Some of us will scrutinize the codes, review, make suggestions and eventually include (merge) them into the main project repo.
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Repeat 3-4 above for a particular exercise. Repeat 1-5 indefinitely till we hit 99/99 projects.
Please see general contribution guidelines for more details.
Please abide by code of conduct guidelines to have an open and friendly open source collaboration.
Goal: 99 Projects
Current: 1 Project
Some of the libraries (and their versions) we are using:
- Python (>= 3.6)
- NumPy (>= 1.18.5)
- Pandas (>= 1.0.5)
- Matplotlib (>= 3.2.2)
- Seaborn (>= 0.10.1)
- Scikit-learn (>= 0.22.2)
- Tensorflow (>= 2.2.0)
- PyTorch (>= 1.5.1)
If you want to get in touch with us, say hi on our discord/gitter chatroom:
This project is inspired by Unnit Metaliya’s answer on quora: https://qr.ae/pNK0FW
For credits, these are the two repos (one for C and one for React) where I got the idea from:
This repo is covered under The MIT License.