In this repo, I use python 3.7.*, feel free to ask me, add new issue and fork grinning.
See also the list of contributors who participated in this project.
- Python >= 3.7.
- pip3
A step by step series of examples that tell you how to get a development env running
- clone the repo to your local machine using
$ git clone https://github.com/SalAlba/machine-learning
$ cd machine-learning
- create virtual env and run using
$ virtualenv venv
$ source venv/bin/activate
- install all requirements using
$ pip install -r requirements.txt
Machine Learning Project Checklist [src 1.1.]
- Frame the Problem and Look at the Big Picture.
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Define the objective (target) in business terms.
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How will your solution be used?
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What are the current solutions/workarounds (if any)?
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How should you frame (category) this problem (supervised/unsupervised, online/offline, etc.)?
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How should performance be measured?
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Is the performance measure aligned with the business objective?
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What would be the minimum performance needed to reach the business objective?
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What are comparable problems? Can you reuse experience or tools?
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Is human expertise available?
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How would you solve the problem manually?
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List the assumptions you (or others) have made so far.
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Verify assumptions if possible.
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Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.
This project is licensed under the MIT License - see the LICENSE.md file for details, Copyright 2020 © Salem Albarudy.