BizAcuity

APRIL 28, 2019

is delinquent as of June 30th, 2017. By clubbing various techniques like data mining, machine learning, artificial intelligence and statistical modelling, it makes predictions about events in the future. An improvement of 50% in debt collection was seen in just 3 months time, that too without any loss on customer interaction.

Predictive Analytics 98

Predictive Analytics Analytics Big Data Data mining 98

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

Peter James Thomas

AUGUST 12, 2018

Pertinence and fidelity of metrics developed from Data. Metrics are seldom reliant on just one data element, but are often rather combinations. There are often compromises to be made in defining metrics. Integrity of statistical estimates based on Data. For example: Is this a good way to define New Business Growth?

Metrics 49

Metrics Statistics Data Quality Measurement 49

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

On the one hand, basic statistical models (e.g. TF Lattice offers semantic regularizers that can be applied to models of varying complexity, from simple Generalized Additive Models, to flexible fully interacting models called lattices, to deep models that mix in arbitrary TF and Keras layers. monotonicity, diminishing returns).

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Domino Data Lab

MAY 8, 2019

Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. Adrian Weller (2017-07-29). “ If your “performance” metrics are focused on predictive power, then you’ll probably end up with more complex models, and consequently less interpretable ones. Challenges for Transparency ”. 2018-06-21).

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

OCTOBER 23, 2019

As a result, there has been a recent explosion in individual statistics that try to measure a player’s impact. Knowing that the ultimate goal is to compare the social-media influence and power of NBA players, a great place to start is with the roster of the NBA players in the 2016–2017 season. 05) in predicting changes in attendance.

Statistics 59

Statistics Machine Learning Testing Modeling 59

datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. ARIMA techniques are complex and drawing conclusions from the results may not be as straightforward as for more basic statistical analysis approaches. Data exploded and became big.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361