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 191

Machine Learning Modeling Testing Risk Management 191

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 Data-driven Big Data 350

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

Insight

MARCH 12, 2020

In 2013, Robert Galbraith?—?an The most powerful approach for the first task is to use a ‘language model’ (LM), i.e. a statistical model of natural language. It is worth keeping in mind that the choice of threshold will impact downstream metrics like precision as well as shifting the size of our dataset. an aspiring author?—?finished

Modeling 59

Modeling Metadata Publishing Sales 59

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 107

Data Processing Dashboards Machine Learning Management 107

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

Sisense

JUNE 26, 2020

It will get us to the complete statistical data for each feature. Previously, he held leadership roles in analytics and operations, including launching the company’s first paid SaaS offerings at Square and helping Tremor Video IPO in 2013. We have three methods for exploratory data analysis: Univariate analysis. Bivariate analysis.

Visualization 97

Visualization Unstructured Data Measurement Data-driven 97