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This repository provides a basic understanding of how to arrange your Machine Learning projects

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Machine_learning_basics

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  • The data files train.csv and test.csv contain gray-scale images of hand-drawn digits, from zero through nine.
  • Each image is 28 pixels in height and 28 pixels in width, for a total of 784 pixels in total. Each pixel has a single pixel-value associated with it, indicating the lightness or darkness of that pixel, with higher numbers meaning darker. This pixel-value is an integer between 0 and 255, inclusive.

About the repo folders

  • models/: This folder keeps all the trained models
  • src/: All the python scripts asscociated with the projects are kept here.
  • create_folds.py : Its the same as the train.csv though the difference is that create_folds.py creates a a CSV which is shuffled and has a new column called Kfold.
  • config.py : This python script is used to avoid hardcoding such as the path to the training data and saving of the models.
  • model_dispatcher.py : This script contains various models that will be used for training of our model example DecisionTree, RandomForest etc.

This project is Licensed to Apache.

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This repository provides a basic understanding of how to arrange your Machine Learning projects

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