Data Science 101

OCTOBER 31, 2019

This data alone does not make any sense unless it’s identified to be related in some pattern. Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). The choice of these metrics depends on the nature of the problem.

Data mining 77

Data mining KDD Data Science Forecasting 77

Domino Data Lab

DECEMBER 4, 2020

Approximating the region under the graph of as a series of trapezoids and calculating the sum of their area (in the case of non-uniformly distributed data points) is given by. Having calculated AUC/AUMC, we can further derive a number of useful metrics like: Total clearance of the drug from plasma. Mean residence time. and many others.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

The Unofficial Google Data Science Blog

JANUARY 14, 2016

by AMIR NAJMI Running live experiments on large-scale online services (LSOS) is an important aspect of data science. Because individual observations have so little information, statistical significance remains important to assess. We must therefore maintain statistical rigor in quantifying experimental uncertainty.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

In this post we explore why some standard statistical techniques to reduce variance are often ineffective in this “data-rich, information-poor” realm. Despite a very large number of experimental units, the experiments conducted by LSOS cannot presume statistical significance of all effects they deem practically significant.

Experimentation 40

Experimentation Metrics Statistics Measurement 40