Smart Data Collective

MARCH 23, 2022

However, we have witnessed a significant uptick in ADA cases being filed against website owners since 2017. Most of the time, this entails launching new ad campaigns, creating blogs to drive organic traffic, and investing in SEO to help your store rank higher in SERPS. between Q1 of 2017 and Q1 of 2018. That’s a lot of cash!

Cost-Benefit 100

Cost-Benefit Data mining Sales Testing 100

O'Reilly on Data

JANUARY 22, 2019

In this blog post, we explore three types of errors inherent in all financial models, with a simple example of a model in TensorFlow Probability (TFP). They trade the markets using quantitative models based on non-financial theories such as information theory, data science, and machine learning. Finance is not physics. Not even close.

Modeling 133

Modeling Finance Uncertainty Data mining 133

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). In this blog post we talked about why working with imbalanced datasets is typically problematic, and covered the internals of SMOTE – a go-to technique for up-sampling minority classes.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

BizAcuity

FEBRUARY 8, 2019

Analyzing raw data, data mining, analytical processing, querying and reporting – these are some of the many things that business intelligence lets an organization achieve. trillion – from their competitors that are still banking on data to make and enforce business decisions.

Business Intelligence 69

Business Intelligence Data mining Data-driven Software 69

BizAcuity

APRIL 28, 2019

is delinquent as of June 30th, 2017. With Big Data, it is possible to acquire and segregate data with laser sharp focus with respect to one singular debtor. By clubbing various techniques like data mining, machine learning, artificial intelligence and statistical modelling, it makes predictions about events in the future.

Predictive Analytics 98

Predictive Analytics Analytics Big Data Data mining 98

Domino Data Lab

AUGUST 1, 2021

Instead, you should focus on how techniques like PDPs and LIME can be used to gain insights into the model’s inner workings and how you can add those to your data science toolbox. In IJCAI 2017 Workshop on Explainable Artificial Intelligence (XAI), pages 24–30, Melbourne, Australia, 2017. References. Explainable planning.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

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