Corinium

JUNE 6, 2019

It is also important to have a strong test and learn culture to encourage rapid experimentation. Measure user adoption and engagement metrics to not just understand products take-up, but also to enhance the overall product propositions. What advances do you see in Visual Analytics in the next five years?

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

The Unofficial Google Data Science Blog

APRIL 23, 2024

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Occam's Razor

JULY 24, 2018

work (collection, processing, reporting, analysis), processes, org structure, governance models, last-mile gaps , metrics ladders of awesomeness , and… so… much… more. Remember, tools, work, processes, org structure, governance models, last-mile gaps, metrics ladders of awesomeness, and… so… much… more. The Implications of Complexity.

Analytics 93

Analytics Metrics Strategy Measurement 93

O'Reilly on Data

APRIL 19, 2021

We’ll look at this later, but being able to reproduce experimental results is critical to any science, and it’s a well-known problem in AI. In contrast, in our 2018 report, Asia was behind in mature practices, though it had a markedly higher number of respondents in the “early adopter” or “exploring” stages. Maturity by Continent.

Enterprise 356

Enterprise Modeling Risk Manufacturing 356

Domino Data Lab

FEBRUARY 4, 2019

Spoiler alert: a research field called curiosity-driven learning is emerging at the nexis of experimental cognitive psychology and industry use cases for machine learning, particularly in gaming AI. Ensure a culture that supports a steady process of learning and experimentation. I double-dare you not to visualize that cohort!

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Domino Data Lab

MAY 8, 2019

2018-06-21). On the other hand, as Lipton emphasized, while the tooling produces interesting visualizations, visualizations do not imply interpretation. ML model interpretability and data visualization. Business stakeholders cannot rely on visualizations to interpret the ML models that their data science teams produce.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

AUGUST 22, 2019

Human brains are not well suited to visualizing anything in greater than three dimensions. Visualizing data using t-SNE. We like the ROC AUC for two reasons: It blends together two useful metrics—true positive rate and false positive rate—into a single summary value. we do not need to consider all of the dimensions. Example 11.9

Deep Learning 111

Deep Learning Modeling Metrics Testing 111