Machine_Learning_Framework

STEPS:

1. Constructing Framework: Here we create folders and python files.
2. Gather Data and build cross-validation {create_folds.py}
3. Training our Models {train.py}
4. Inference: Train all Folds and predict the test dataset {predict.py}

Cross-Validation Approaches {cross_validation.py}

• binary_classification
• multi-class classification
• multilabel classification
• single column regression
• multi column regression
• holdout

Categorical Data Approaches {categorical.py}

PREPROCESSING

• label encoding
• one-hot encoding
• binarization

IN MODEL