CIO Business Intelligence

APRIL 12, 2024

Computer vision skills are important for helping AI systems with image classification, object detection and recognition, 3D reconstructions, biometric data collection, and motion tracking and analysis.

Deep Learning 124

Deep Learning IT Machine Learning IoT 124

Occam's Razor

APRIL 8, 2013

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. Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Testing out a new feature.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Domino Data Lab

MAY 20, 2021

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. Their tests are performed using C4.5-generated 1988), E-state data (Hall et al., The unreasonable effectiveness of data.

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. Here’s where I get baffled by people who use words such as agile or lean to describe process for data science.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

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

AUGUST 1, 2021

After forming the X and y variables, we split the data into training and test sets. Looking at the target vector in the training subset, we notice that our training data is highly imbalanced. PDPs for the bicycle count prediction model (Molnar, 2009). X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2,

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

datapine

JANUARY 31, 2022

The companies that are most successful at marketing in both B2C and B2B are using data and online BI tools to craft hyper-specific campaigns that reach out to targeted prospects with a curated message. Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214