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Inside this repository, you will find a file called `./notebook/problems.ipynb` with the exercises you need to finish to complete it.
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Use this template for creating Jupyter notebooks compatible with Gitpod and local environments.
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## 🌱 How to start this project
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Once the Gitpod workspace has successfully loaded, it will install the most common dependencies used in a typical notebook.
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The easiest way to start working on this project is by using Gitpod:
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## How to use
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1. Make a fork of [this repository](https://github.com/breatheco-de/algorithm-optimization-project-machine-learning) into your github account.
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2. Open the recently created fork on Gitpod by using the [Gitpod button extension](https://www.gitpod.io/docs/browser-extension/).
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3. Once Gitpod VSCode has finished opening you can go ahead and open the `problems.ipynb` file and start solving each exercise inside the notebook.
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- Add your notebooks in the `./notebbook` folder.
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- Open the notebooks and run the python code.
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## 🚛 How to deliver this project
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## Default dependencies
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Once you are finished solving the exercises make sure to commit your changes, push to your repository fork and go to 4Geeks.com to upload the repository link.
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```
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# Base ----------------------------------------
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pandas>=1.1.4
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numpy>=1.18.5
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opencv-python>=4.1.2
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matplotlib>=3.2.2
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ipyleaflet>=0.14.0
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sympy>=1.10.1
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# Solutions
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# Machine learning ----------------------------
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sklearn
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```
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We also incorporated the solutions files `./notebook/*-solution[n].ipynb` that we strongly suggest you only use if you are stuck for more than 30min or if you have already finished and want to compare it with your approach.
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