O'Reilly on Data

JANUARY 22, 2019

They trade the markets using quantitative models based on non-financial theories such as information theory, data science, and machine learning. Whether financial models are based on academic theories or empirical data mining strategies, they are all subject to the trinity of modeling errors explained below. References.

Modeling 213

Modeling Finance Uncertainty Data mining 213

Smart Data Collective

MARCH 23, 2022

However, we have witnessed a significant uptick in ADA cases being filed against website owners since 2017. Evan Morris of Towards Data Science discussed this in one of his recent articles. between Q1 of 2017 and Q1 of 2018. AI technology has made it easier to conform to ADA standards. That’s a lot of cash!

Cost-Benefit 128

Cost-Benefit Data mining Sales Testing 128

CIO Business Intelligence

AUGUST 11, 2023

Licensed by MIT, SpaCy was made with high-level data science in mind and allows deep data mining. Data Science: Natural Language Processing in Python from Udemy. SpaCy , an open-source library for advanced natural language processing explicitly designed for production use rather than research.

Unstructured Data 142

Unstructured Data Machine Learning Data Science Data mining 142

datapine

NOVEMBER 27, 2019

Accordingly, predictive and prescriptive analytics are by far the most discussed business analytics trends among the BI professionals, especially since big data is becoming the main focus of analytics processes that are being leveraged not just by big enterprises, but small and medium-sized businesses alike. BN by 2023, with a CAGR of 13.6%

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Domino Data Lab

MAY 20, 2021

note that this variant “performs worse than plain under-sampling based on AUC” when tested on the Adult dataset (Dua & Graff, 2017). Data mining for direct marketing: Problems and solutions. Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining, 73–79. References.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

The Unofficial Google Data Science Blog

JULY 22, 2020

Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining. Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 2017. [4] Causal inference in statistics, social, and biomedical sciences. 2] Scott, Steven L.

Experimentation 96

Experimentation Statistics Testing Knowledge Discovery 96

The Unofficial Google Data Science Blog

APRIL 23, 2024

arXiv: Optimization and Control, 2017. [12] Estimating Uncertainty for Massive Data Streams. Improving the sensitivity of online controlled experiments by utilizing pre-experiment data. Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, WSDM ’13, page 123–132, New York, 2013. [28]

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52