GitHub - IsabelCHM/MachineLearningPython: Part 1: Applied Machine Learning algorithms using the Python language to predict whether adult Pima Indian females are diagnosed with diabetes. Feature engineering was conducted using Pearson correlations. Logistic regression, KNN and Decision Tree classification models were used. Part 2: My team and I trained a Convolutional Neural Network model using data from the Fruits for Object Detection dataset on Kaggle. We observed that using data augmentation as well as reducing the size of the images when resizing the data led to an increase in accuracy of our model when it was validated against a test dataset.

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Name		Name	Last commit message	Last commit date
Latest commit History 4 Commits
2. Part 2 CNN		2. Part 2 CNN
CA Project Correlation FE Part 1 All Models.ipynb		CA Project Correlation FE Part 1 All Models.ipynb
diabetes.csv		diabetes.csv

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Part 1: Applied Machine Learning algorithms using the Python language to predict whether adult Pima Indian females are diagnosed with diabetes. Feature engineering was conducted using Pearson correlations. Logistic regression, KNN and Decision Tree classification models were used. Part 2: My team and I trained a Convolutional Neural Network mode…

machine-learning python3