O'Reilly on Data

DECEMBER 12, 2019

For model training and selection, we recommend considering fairness metrics when selecting hyperparameters and decision cutoff thresholds. 1] “All models are wrong, but some are useful.” — George Box, Statistician (1919 – 2013). [2] 17] Hopefully some of these techniques will work for you and your team.

Machine Learning 282

Machine Learning Modeling Testing Risk Management 282

Ontotext

MARCH 24, 2021

For these reasons, we have applied semantic data integration and produced a coherent knowledge graph covering all Bulgarian elections from 2013 to the present day. Easily accessible linked open elections data.

Statistics 142

Statistics Publishing Data Processing Metrics 142

datapine

MAY 14, 2019

In 2013, less than 0.5% For those embarking on a journey to master the art of the ‘R’ language – a statistical computing program and framework for increased business intelligence-based success – Advanced R is intuitive, easy to follow, and will give you a well-rounded overview of this invaluable area of data science.

Data Science 350

Data Science Machine Learning Big Data Data-driven 350

DataKitchen

JUNE 24, 2021

Chapin shared that even though GE had embraced agile practices since 2013, the company still struggled with massive amounts of legacy systems. One of the keys for our success was really focusing that effort on what our key business initiatives were and what sorts of metrics mattered most to our customers. Take a show-me approach.

Metrics 211

Metrics ROI Measurement Cost-Benefit 211

AWS Big Data

MARCH 13, 2024

Each service implements k-nearest neighbor (k-NN) or approximate nearest neighbor (ANN) algorithms and distance metrics to calculate similarity. You will see the Ray dashboard and statistics of the jobs and cluster running. You can track metrics from here. He entered the big data space in 2013 and continues to explore that area.

Data Processing 132

Data Processing Dashboards Machine Learning Metrics 132

Domino Data Lab

APRIL 21, 2021

In contrast, the decision tree classifies observations based on attribute splits learned from the statistical properties of the training data. Machine Learning-based detection – using statistical learning is another approach that is gaining popularity, mostly because it is less laborious. from sklearn import metrics.

Statistics 69

Statistics Machine Learning Modeling Metrics 69

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