Remove 2016 Remove Interactive Remove Metrics Remove Predictive Modeling
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Tackling Bias in Machine Learning

Insight

Bias in Machine Learning Algorithms (Bottom Photos Source: ProPublica ; Top Photos Source: Pexels.com) Biases in predictive modeling are a widespread issue Machine learning and AI applications are used across industries, from recommendation engines to self-driving cars and more.

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Techniques for Collecting, Prepping, and Plotting Data: Predicting Social Media-Influence in the NBA

Domino Data Lab

Knowing that the ultimate goal is to compare the social-media influence and power of NBA players, a great place to start is with the roster of the NBA players in the 2016–2017 season. One of the things this data set doesn’t have, however, is a single metric to rank both offensive and defensive performance in a single statistic.

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Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

GloVe and word2vec differ in their underlying methodology: word2vec uses predictive models, while GloVe is count based. Instead, we recommend using the bokeh library to create a highly interactive—and actionable—plot, as with the code provided in Example 11.11. Interactive bokeh plot of two-dimensional word-vector data.

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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

The need for interaction – complex decision making systems often rely on Human–Autonomy Teaming (HAT), where the outcome is produced by joint efforts of one or more humans and one or more autonomous agents. 2016) for an example of this technique (LIME). PDPs for the bicycle count prediction model (Molnar, 2009).

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