Analytics Vidhya

FEBRUARY 20, 2023

Introduction We are living in an era of massive data production. When you think about it, almost every device or service we use generates a large amount of data (for example, Facebook processes approximately 500+ terabytes of data per day).

Knowledge Discovery 288

Knowledge Discovery Data mining Analytics KDD 288

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

Data Science 101

DECEMBER 11, 2019

This weeks guest post comes from KDD (Knowledge Discovery and Data Mining). Every year they host an excellent and influential conference focusing on many areas of data science. Honestly, KDD has been promoting data science way before data science was even cool. 1989 to be exact. The details are below.

KDD 81

KDD Knowledge Discovery Data mining Data Science 81

FineReport

JULY 16, 2021

Among these problems, one is that the third party on market data analysis platform or enterprises’ own platforms have been unable to meet the needs of business development. With the advancement of information construction, enterprises have accumulated massive data base. Data Warehouse. Data Mining.

Business Intelligence 98

Business Intelligence Informatics Data Warehouse Data mining 98

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. From Google. There are two points here.

Knowledge Discovery 98

Knowledge Discovery Visualization Data mining Reporting 98

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. If, however, the dataset is imbalanced with a class ratio of 100:1, this means that it contains only 100 examples of the minority class.

Machine Learning 136

Machine Learning Metrics Data mining Data Science 136

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

A small but persistent team of data scientists within Google’s Search Ads has been pursuing item #2 since about 2008, leading to a much improved understanding of the long-term user effects we miss when running typical short A/B tests. In this blog post, we summarize that paper and refer you to it for details.

Modeling 63

Modeling Experimentation Knowledge Discovery KDD 63