ditat-llc / ditat_ml

ditat.io Machine Learning Framework

ditat_ml

ditat.io framework for deployment of machine learning models.

For further information visit ditat.io

Installation (and updates)

pip install git+https://github.com/ditat-llc/ditat_ml.git --upgrade

Using ssh

pip install git+ssh://[email protected]/ditat-llc/ditat_ml.git --upgrade

The other option is to clone the repo and install it locally.

pip install -e ./ditat_ml

Usage

This framework gives you the flexibility to operate with high-level api (Pipeline) and also with its low-level functions, among others.

High-level usage

Train and Test

from ditat_ml import Pipeline

p = Pipeline()
p.load_data(path='dataset.csv')
p.load_X_y(X_columns, y_columns)
p.preprocessing(**mappings ) # Check documentation for more details.
p.scale()

p.model = YOUR_MODEL_CHOICE

p.train()

Deploy

One you are satisfied with your model's performance, you can deploy it.

p.deploy(name='my_model')

Predict

from ditat_ml import Pipeline

p = Pipeline()
predictions = p.predict(path='dataset.csv', model_name='my_model')

Low-level usage

You can also use its low-level functions to give you more flexibility.

from ditat_ml import utility_functions