machine-learning

In this repo, I use python 3.7.*, feel free to ask me, add new issue and fork grinning.

Authors

• Salem Albarudy - Website | GitHub | Linkedin

See also the list of contributors who participated in this project.

Getting Started

Prerequisites

• Python >= 3.7.
• pip3

Installing

A step by step series of examples that tell you how to get a development env running

1. clone the repo to your local machine using

    $ git clone https://github.com/SalAlba/machine-learning
    $ cd machine-learning

2. create virtual env and run using

    $ virtualenv  venv
    $ source venv/bin/activate

3. install all requirements using

    $ pip install -r requirements.txt

Notes / Things you should to know

Machine Learning Project Checklist [src 1.1.]

1. Frame the Problem and Look at the Big Picture.

   1. Define the objective (target) in business terms.

   2. How will your solution be used?

   3. What are the current solutions/workarounds (if any)?

   4. How should you frame (category) this problem (supervised/unsupervised, online/offline, etc.)?

   5. How should performance be measured?

   6. Is the performance measure aligned with the business objective?

   7. What would be the minimum performance needed to reach the business objective?

   8. What are comparable problems? Can you reuse experience or tools?

   9. Is human expertise available?

   10. How would you solve the problem manually?

   11. List the assumptions you (or others) have made so far.

   12. Verify assumptions if possible.

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

License

This project is licensed under the MIT License - see the LICENSE.md file for details, Copyright 2020 © Salem Albarudy.

Resources

1. Books

• [1.1.] Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems 1st Edition

2. Websites

• [2.1.]

3. Papers

• [3.0.] ...