Every Python developer knows some or all of these libraries, because they’re stable, reliable, and excellent at what they do.

When working with production data science code it can be handy to have a plotting tool that does not rely on graphics dependencies or works only in a Jupyter notebook. The plot function accepts a ...

📌 Important Notice: Please ensure that dataset files are placed in the data directory before executing run.py. For emphasis, we've incorporated an error ...

Machine learning enthusiast. Research engineer at Skoltech. Do you remember the time when the Flappy Bird appeared on the smartphones screens? This game has started the era of casual games with very ...

Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...