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Short tutorial introducing machine learning to students
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.ipynb_checkpoints
Ethics in AI.pdf
Introduction to Machine Learning.pdf
MLTutorial_DIY-Solution.ipynb
MLTutorial_DIY.ipynb
MLTutorial_Example.ipynb
README.md
data_numerical.csv
iris.csv

README.md

MLTutorial_FAMU_FSU_COE

This repo contain materials for a tutorial on machine learning presented by Diandra Prioleau, Kiana Alikhademi, Brianna Richardson and Emma Drobina at the one-day visit from FAMU-FSU COE students at Human Experience Research Lab at University of Florida in March 2019.

All tutorial materials will use python and jupiter notebooks. Students will be introduced to machine learning domain and do a step-by-step tutorial on well-known Iris dataset along with the presenters. Further, they will used the acquired knowledge to predic breast cancer using dataset at following link: https://archive.ics.uci.edu/ml/datasets/breast+cancer+wisconsin+(original)

Requirements:

Option 1:Anaconda is a distribution environment which makes multiple helpful IDEs such as jupyter notebooks, spyder and etc accessible. You can install Anaconda by simply following the steps in the following link. https://docs.anaconda.com/anaconda/install/

Option 2: if you do not want to install Anaconda, you need to install python and jupiter notebooks separately. To install jupiter notebook use the steps mentioned in the following link: https://jupyter.org/install To install python 3.7.2 libraries, first download it from the follwing link: https://www.python.org/downloads/

Make sure to install the following libraries: https://scikit-learn.org https://pandas.pydata.org

You can use the following command to install any package in python: pip install

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