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The trinity of errors in financial models: An introductory analysis using TensorFlow Probability

O'Reilly on Data

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.

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eCommerce Companies Use AI to Ensure their Sites Are ADA Compliant

Smart Data Collective

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!

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What is NLP? Natural language processing explained

CIO Business Intelligence

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.

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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

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%

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

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.

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Changing assignment weights with time-based confounders

The Unofficial Google Data Science Blog

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.

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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

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]