Our first work in Machine Learning.
During our winter break we took an extracurricular course about Machine Learning and Python. Here we learned how to use Python and it's libraries for Machine Learning, in order to finish up the course programming a small Collaboratory document where we applied everything we have learned. This project uses the Seattle Terry Stops dataset in order to extract the data needed to train our models. Using all the data available we decided to predict whether a subject would be arrested by the police.
A lot of things. To mention some:
- How to work with Colaboratory enviroment
- Python libraries used in Machine Learning such as Pandas, Matplotlib, Numpy, etc
- Different Machine Learning models
- How to clean a dataset in order to transform it to something a program can understand
- How to set up different models and check out their accuracy
- How to program a basic Neural Network
- Clone this repository in your local repositories using git.
git clone https://github.com/alxe22/Machine_Learning_JEDI_Project-Autumn2018.git
- Add Collaboratory in your Google Drive account.
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Upload to your Google Drive account the finalDocument.ipynb and open it with Collaboratory.
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Upload the dataset into your Collaboratory virtual enviroment to start experimenting with our results.
Do you whant to suggest us anything? Did you find anything that could be improved? Don't be shy and open a new Issue telling us what could be done better 😊
Feel free to read, use or modify all or part of my work without giving me any credit at all. This activity was the final project for an extracurricular course I took during my summer holidays at my university. If you are interested in learning Android or want to learn more visit, the following https://jediupc.com/cursos/.
