workshop-machine-learning-titanic

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workshop-machine-learning-titanic

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This Jupyter Notebook was used to give a workshop about Machine Learning with Python in Brazil with the support of WoMakersCode Community.

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# ML Workshop: exploring survival on the Titanic

This Jupyter Notebook was used to give a workshop about Machine Learning with Python in Brazil with the support of [WoMakersCode Community](https://github.com/WoMakersCode).

The Notebook is a Machine Learning Solution to a Kaggle Competition. You can read more about the challenge here: [Titanic: Machine Learning from Disaster](https://www.kaggle.com/c/titanic/data)

You can access the slides used in the workshop here: [Workshop Slides Presentation](https://docs.google.com/presentation/d/1eCrsY8pIv_QuNHgESFZ19uwhmPx1EcADDQRdX-3mWv8/edit?usp=sharing)

## Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and learning purposes.

### Prerequisites

* Python 3.7
* Jupyter Notebook (I recommend using [Anaconda](https://www.anaconda.com/download/))

### Download/Clone repository

Download or clone this repository to your machine (it includes jupyter notebook and titanic)

### Start your own ```Jupyter Notebook```

**Windows**

Inside your project folder with all the files from this repository, open cmd and run the command ```jupyter notebook```. Your cmd should looke like the image below:

![Image of cmd running Jupyter](https://i.imgur.com/imfl23W.png)

Now, you are all started and it should open a new tab on your browser running Jupyter.

## Authors

* **Carla Vieira** - [@carlaprvieira](https://twitter.com/carlaprvieira)

## Acknowledgments

* [Megan Risdal notebook on Kaggle](https://www.kaggle.com/mrisdal/exploring-survival-on-the-titanic)
* [Classificando Músicas do Spotify com SVM (Com Códigos Python)](http://minerandodados.com.br/index.php/2018/04/04/spotify-svm-python/)
* [Train/Test Split and Cross Validation in Python](https://towardsdatascience.com/train-test-split-and-cross-validation-in-python-80b61beca4b6)
* [Cross-validation: evaluating estimator performance](https://scikit-learn.org/stable/modules/cross_validation.html)

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