In the "Autism Prediction" Folder you will find "Cleaning", "Data", and "Machine Learning Models" folders as well as an images folder which contains screenshots.

This folder contains the original dataset which was procured from Kaggle. It also contains the cleaned dataset, and a cleaned dataset that was generated to support tableau visualizations. This folder also contains two excel files which describe the accuracy and F1 scores and were used for visual generation in Tableau.

This folder contains the python code for the cleaning of our original train dataset as well its cleaning into a format that was ideal for visualization generation.

This folder contains the 6 folders: Decision Tree, Random Forest, Logistic Regression, Support Vector Classifier, Neural Network, and Keras Tuner Neural Network. In each folder you will find 1 or 2 Jupyter Notebook files which contain the code to run the requisite machine learning model. The outcome F1 and Accuracy scores are also calculated.

The Predicting Autism with Machine Learning walks through our project, providing explanations about what autism is, why machine learning models would be useful, and how we conducted the analysis.

We were able to generate machine learning models that could predict autism with 91% accuracy and F1 scores of .81 for autistic individuals and .94 for non autistic individuals. This could be an invaluable tool to the autistic community including parents, teachers and autistic individuals, but could also be improved further.