mads-datasets 0.2.1

Datasets for the master applied data science

MADS Datasets Library

This library provides the functionality to download, process, and stream several datasets.

Installation

This library has been published on PyPi and can be installed with pip or poetry.

# Install with pip
pip install mads_datasets

# Install with poetry
poetry add mads_datasets

Data Types

Currently, it supports the following datasets:

• SUNSPOTS Time-Series data
• IMDB Text data
• FLOWERS Image data
• FASHION MNIST Image data
• GESTURES Time-Series data
• IRIS dataset

Usage

After installation, import the necessary components:

from mads_datasets import DatasetFactoryProvider, DatasetType

You can create a specific dataset factory using the DatasetFactoryProvider.

For instance, to create a factory for the Fashion MNIST dataset:

fashion_factory = DatasetFactoryProvider.create_factory(DatasetType.FASHION)

With the factory, you can download the data, create datasets and provide the datasets wrapped in datastreamers in one command:

streamers = mnistfactory.create_datastreamer(batchsize=32)
train = streamers["train"]
X, y = next(train.stream())

The train.stream() command wil return a generator that will yield batches of data.

You could also create a dataset directly:

dataset = fashion_factory.create_dataset()

Or download the data:

fashion_factory.download_data()