Occam's Razor

APRIL 8, 2013

To win in business you need to follow this process: Metrics > Hypothesis > Experiment > Act. We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. That metric is tied to a KPI.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Smart Data Collective

APRIL 5, 2019

Social media monitoring involves collecting data and is quantifiable. For example, it hones in on metrics in social media like retweets, engagement rates, mention, and story completions. It takes into consideration things that have already happened, and is useful for making changes to your campaigns in the future.

Big Data 79

Big Data Interactive Data-driven Metrics 79

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

Occam's Razor

FEBRUARY 22, 2010

These toolbars also collect limited information about the browsing behavior of the customers who use them, including the pages visited, the search terms used, perhaps even time spent on each page, and so forth. Typically, data collected is anonymous and not personally identifiable information (PII). 6: Self-reported Data.

Metrics 123

Metrics Advertising Reporting Software 123

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. data collection”) show the “process” steps that a team performs, while the boxes (e.g.,

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Occam's Razor

SEPTEMBER 4, 2012

2009 was the year of mobile. If your company has a non-stinky mobile website and mobile app then congratulations: you have successfully solved the problem of 2009! Mobile application analytics solutions provide a very robust set of data about your apps. And travel is by no means unique; try any of your normal brands.

Marketing 144

Marketing Data mining Measurement Strategy 144

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. PDPs for the bicycle count prediction model (Molnar, 2009). Courville, Pascal Vincent, Visualizing Higher-Layer Features of a Deep Network, 2009. Ribeiro, M. Guestrin, C.,

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139