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). Machine learning provides the technical basis for data mining.

Data mining 77

Data mining KDD Data Science Forecasting 77

FineReport

DECEMBER 19, 2019

For super rookies, the first task is to understand what data analysis is. Data analysis is a type of knowledge discovery that gains insights from data and drives business decisions. One is how to gain insights from the data. Data is cold and can’t speak. 6 Key Skills That Data Analysts Need to Master.

Knowledge Discovery 98

Knowledge Discovery Visualization Data mining Reporting 98

Domino Data Lab

MAY 20, 2021

The dataset and code used in this blog post are available at [link] and all results shown here are fully reproducible, thanks to the Domino reproducibility engine, which is part of the Domino Data Science platform. References. Data mining for direct marketing: Problems and solutions. Banko, M., & Brill, E.

Machine Learning 136

Machine Learning Metrics Data mining Data Science 136

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

In this blog post, we summarize that paper and refer you to it for details. References [1] Henning Hohnhold, Deirdre O'Brien, Diane Tang, Focus on the Long-Term: It's better for Users and Business , Proceedings 21st Conference on Knowledge Discovery and Data Mining, 2015. [2] 2] Ron Kohavi, Randal M.

Modeling 63

Modeling Experimentation Knowledge Discovery Testing 63

The Unofficial Google Data Science Blog

JULY 22, 2020

This post considers a common design for an OCE where a user may be randomly assigned an arm on their first visit during the experiment, with assignment weights referring to the proportion that are randomly assigned to each arm. References [1] Kohavi, Ron, Randal M. Henne, and Dan Sommerfield. 2] Scott, Steven L. 2015): 37-45. [3]

Experimentation 96

Experimentation Statistics Testing Knowledge Discovery 96

The Unofficial Google Data Science Blog

JANUARY 14, 2016

The statistical effect size is often defined as [ e=frac{delta}{sigma} ]which is the difference in group means as a fraction of the (pooled) standard deviation (sometimes referred to as “Cohen’s d” ). Further assume $Y_i sim N(mu,sigma^2)$ under control and $Y_i sim N(mu+delta,sigma^2)$ under treatment (i.e. known, equal variances).

Experimentation 42

Experimentation Statistics Metrics Measurement 42

The Unofficial Google Data Science Blog

NOVEMBER 4, 2015

For more on ad CTR estimation, refer to [2]. References [1] Omkar Muralidharan, Amir Najmi "Second Order Calibration: A Simple Way To Get Approximate Posteriors" , Technical Report, Google, 2015. [2] A machine learning system produces an estimated CTR $t_i$ for each query-ad pair. Our method has four steps: Bin by $t$.

KDD 40

KDD Testing Machine Learning Measurement 40