This is the sourcecode of Kaggle's machine learning exercise: Building Machine learning models.
I have used scikit-learn library to create a model. The steps to building and using a model are:
Define: The type of model will be a decision tree
Fit: Captured features from the provided data that are useful for building a model
Predict: Gives the sales price prediction
Evaluate: Determine how accurate the model's predictions are.
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Download fashion training and test datasets using below link: https://www.kaggle.com/zalando-research/fashionmnist#fashion-mnist_train.csv
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Load data, build and evaluate machine learning models using scikit-learn3.Load and explore the MNIST fashion training dataset.
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Split the training dataset into train and validation datasets using 70:30 split
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Experimented with different machine learning algorithms to see if a better model can be build (ensembles, bagging, boosting, random forests, xgboostclassifier)