In this talk from SciPy 2017, Daniil Pakhomov goes through the theory of the recent state-of-the-art methods for image segmentation based on FCNs and presents his library which aims to provide a simplified way for users to apply these methods for their own problems.
The map, filter, and reduce functions in Python simplify the job of working with lists. In this lesson, learn how to use each function.
Decision Tree classifiers are intuitive, interpretable, and one of the most effective supervised learning algorithms.
In this episode, Josh Gordon walk you through writing a Decision Tree classifier from scratch, in pure Python, introducing you to concepts including Decision Tree Learning, Gini Impurity, and Information Gain.
From the EuroPython Conference July 2017, Anjana Vakil explains the beauty and simplicity of lambda functions.