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

KDnuggets

DECEMBER 12, 2019

ACM SIGKDD Invites Industry and Academic Experts to Submit Advancements in Data Mining, Knowledge Discovery and Machine Learning for 26 th Annual Conference in San Diego.

KDD 67

KDD Knowledge Discovery Data Science Data mining 67

Domino Data Lab

MAY 20, 2021

Machine Learning algorithms often need to handle highly-imbalanced datasets. A weighted nearest neighbor algorithm for learning with symbolic features. Machine Learning, 57–78. UCI machine learning repository. Machine learning for the detection of oil spills in satellite radar images.

Machine Learning 136

Machine Learning Metrics Data mining Data Science 136

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

The Unofficial Google Data Science Blog

NOVEMBER 4, 2015

by OMKAR MURALIDHARAN Many machine learning applications have some kind of regression at their core, so understanding large-scale regression systems is important. But most common machine learning methods don’t give posteriors, and many don’t have explicit probability models. For more on ad CTR estimation, refer to [2].

KDD 40

KDD Testing Machine Learning Measurement 40

Domino Data Lab

AUGUST 1, 2021

The interest in interpretation of machine learning has been rapidly accelerating in the last decade. This can be attributed to the popularity that machine learning algorithms, and more specifically deep learning, has been gaining in various domains. Conference on Knowledge Discovery and Data Mining, pp.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139