Domino Data Lab

MAY 20, 2021

Further, imbalanced data exacerbates problems arising from the curse of dimensionality often found in such biological data. Insufficient training data in the minority class — In domains where data collection is expensive, a dataset containing 10,000 examples is typically considered to be fairly large.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Domino Data Lab

MAY 8, 2019

The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. Instead, consider a “full stack” tracing from the point of data collection all the way out through inference. ML model interpretability and data visualization. . – back to the structure of the dataset.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

datapine

JANUARY 31, 2022

BI software uses algorithms to extract actionable insights from a company’s data and guide its strategic decisions. BI users analyze and present data in the form of dashboards and various types of reports to visualize complex information in an easier, more approachable way. 5) Find improvement opportunities through predictions.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Domino Data Lab

AUGUST 1, 2021

Because of its architecture, intrinsically explainable ANNs can be optimised not just on its prediction performance, but also on its explainability metric. Skater provides a wide range of algorithms that can be used for visual interpretation (e.g. PDPs for the bicycle count prediction model (Molnar, 2009).

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139