Cloudera

JUNE 2, 2022

This blog aims to answer two questions: What is a universal data distribution service? Why does every organization need it when using a modern data stack? In the modern data stack, there is a diverse set of destinations where data needs to be delivered. This presents a unique set of challenges.

Enterprise 107

Enterprise Data Lake Data Collection Data-driven 107

CIO Business Intelligence

JULY 13, 2022

This blog aims to answer two questions: What is a universal data distribution service? Why does every organization need it when using a modern data stack? In the modern data stack, there is a diverse set of destinations where data needs to be delivered. This presents a unique set of challenges.

Enterprise 63

Enterprise Data Lake Data Collection Data-driven 63

Data Science 101

JANUARY 15, 2020

Bias ( syatematic unfairness in data collection ) can be a potential problem in experiments and we need to take it into account while designing experiments. Suppose we want to compare the literate data of a country across decades. Let the number of literate people increased by 5000 in 2010-2020 whereas 3500 in 2000-2010.

Experimentation 96

Experimentation Statistics Measurement Testing 96

Insight

MARCH 27, 2019

Ways to get better data Efforts to improve the quality of data often have a higher return on investment than efforts to enhance models. There are three main ways to improve data: collecting more data, synthesizing new data, or augmenting existing data. DeepAugment takes 4.2 x2large instance.

Optimization 75

Optimization Cost-Benefit Modeling Strategy 75

The Unofficial Google Data Science Blog

APRIL 17, 2017

Due to multiple changes to the scale of the values depicted on the vertical axis, “Results Pages” values, which reflect search query volume, at the rightward end of the plot (corresponding to July 2004) are 2000 times larger than the values depicted at the leftward end (corresponding to November 1998). 2000): 451-476. [6] 2014): 276.

Forecasting 83

Forecasting Modeling Statistics Uncertainty 83

Domino Data Lab

MAY 20, 2021

Insufficient training data in the minority class — In domains where data collection is expensive, a dataset containing 10,000 examples is typically considered to be fairly large. In Proceedings of the 2000 International Conference on Artificial Intelligence (ICAI), 111–117. Protein classification with imbalanced data.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

Implicitly, there was a prior belief about some interesting causal mechanism or an underlying hypothesis motivating the collection of the data. As computing and storage have made data collection cheaper and easier, we now gather data without this underlying motivation.

Experimentation 61

Experimentation Testing Statistics Metrics 61