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Adjusting for Bias with Procedural Data

Adjusting for Bias with Procedural Data

By: Shesh Narayan Gupta, Nicholas Bear Brown 3D software are now capable of producing highly realistic images that look nearly indistinguishable from real images. This raises the question: can real datasets be enhanced with 3D-rendered data? We investigate this...

Gauguin

Gauguin

Gauguin is a project with five objectives: To automate EDA To create a python based AutoEDA tool similar to the many AutoML frameworks where a user uploads some data selects a target of interest and the tool creates thousands of visualizations giving insight into the...

Kindo

Kindo

Kindo is a reinforcement learning high-level API enabling developers and analysts to use Stable Baselines 3 and TF-Agents algorithms. Stable Baselines 3 is powered by PyTorch. TF-Agents is powered by Tensorflow 2.X Kindo enables to train models using both Tensorflow...

Typography-MNIST (TMNIST)

Typography-MNIST (TMNIST)

This dataset is inspired by the MNIST database for handwritten digits. It consists of images representing digits from 0-9 produced using 2,990 google fonts files. The dataset consists of a single file: TMNIST_Data.csvThis file consists of 29,900 examples with labels...

PANOSE Typography

PANOSE Typography

The PANOSE dataset annotates thousands of typefaces with 10 concatenated numeric values in which a typographer classifies a type by Serif Style, Weight, Proportion, Contrast, Stroke Variation, Arm Style, Letterform, Midline, and X-height.     

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