Data mining, Deep Learning, Measurement and Workshop

Meta-Learning For Better Machine Learning

Rocket-Powered Data Science

DECEMBER 16, 2018

From the second example above, Neural Network modeling, there are also many different preliminary tasks and parameterizations of the network that need to be decided and acted on before the cold start iterations on the edge weights can begin: How will we measure the supervised learning model’s accuracy?

Machine Learning

Machine Learning Metrics Optimization Data Science

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

Domino Data Lab

AUGUST 1, 2021

The interest in interpretation of machine learning has been rapidly accelerating in the last decade. This can be attributed to the popularity that machine learning algorithms, and more specifically deep learning, has been gaining in various domains. Methods for explaining Deep Learning. See Wei et al.

Modeling

Modeling Deep Learning Machine Learning Knowledge Discovery

Data Leaders Brief

Meta-Learning For Better Machine Learning

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

Webinars

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