Occam's Razor

JUNE 4, 2018

I mean developing and inserting a subtle collection of gentle nudges that can help increase the conversion rate by a statistically significant amount. Not easy, but your business model has to change to survive.). Checkout the Kimbao Sauvignon Blanc you can see sales and would buy it again rates since 2011. Add to Basket!

Strategy 124

Strategy Cost-Benefit Testing Sales 124

Peter James Thomas

AUGUST 12, 2018

Integrity of statistical estimates based on Data. Having spent 18 years working in various parts of the Insurance industry, statistical estimates being part of the standard set of metrics is pretty familiar to me [7]. The thing with statistical estimates is that they are never a single figure but a range. million ± £0.5

Metrics 49

Metrics Statistics Data Quality Measurement 49

Occam's Razor

SEPTEMBER 13, 2016

Bonus #2: The Askers-Pukers Business Model. If you are curious, here is a April 2011 post: The Difference Between Web Reporting And Web Analysis. Ok, maybe statistical modeling smells like an analytical skill. Bonus #2: The Askers-Pukers Business Model. Three thoughts that explain the Econsultancy/Lynchpin graph.

Modeling 127

Modeling Reporting Strategy Consulting 127

Domino Data Lab

JANUARY 6, 2019

Also, clearly there’s no “one size fits all” educational model for data science. Laura Noren, who runs the Data Science Community Newsletter , presented her NYU postdoc research at JuptyerCon 2018, comparing infrastructure models for data science in research and education. Downey (2011). Python Data Science Handbook.

Data Science 56

Data Science Machine Learning Reporting Visualization 56

Domino Data Lab

AUGUST 22, 2019

The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. While the field of computational linguistics, or Natural Language Processing (NLP), has been around for decades, the increased interest in and use of deep learning models has also propelled applications of NLP forward within industry.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

The Unofficial Google Data Science Blog

JULY 11, 2017

SCOTT Time series data are everywhere, but time series modeling is a fairly specialized area within statistics and data science. This post describes the bsts software package, which makes it easy to fit some fairly sophisticated time series models with just a few lines of R code. by STEVEN L. Forecasting (e.g.

Forecasting 64

Forecasting Statistics Modeling Software 64

Domino Data Lab

OCTOBER 9, 2019

According to David Madigan, the former chair of Department of Statistics and current Dean of Faculty of Arts and Sciences and Professor of Statistics at Columbia University, a good metric for determining the optimal number of clusters is Hartigan’s rule (J. shows the Gap statistic for a number of different clusters.

Statistics 100

Statistics Machine Learning Metrics Measurement 100

IBM Big Data Hub

OCTOBER 12, 2023

Early iterations of the AI applications we interact with most today were built on traditional machine learning models. These models rely on learning algorithms that are developed and maintained by data scientists. For example, Apple made Siri a feature of its iOS in 2011. IBM watsonx.ai Explore watsonx.ai

Machine Learning 68

Machine Learning Deep Learning Interactive Modeling 68

The Unofficial Google Data Science Blog

JULY 18, 2023

Editor's note : The relationship between reliability and validity are somewhat analogous to that between the notions of statistical uncertainty and representational uncertainty introduced in an earlier post. Throughout, we’ll refer to our model-derived measurement of inter-rater reliability as the Intraclass Correlation Coefficient (ICC).

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

The Unofficial Google Data Science Blog

MAY 31, 2016

Statistical power is traditionally given in terms of a probability function, but often a more intuitive way of describing power is by stating the expected precision of our estimates. This is a quantity that is easily interpretable and summarizes nicely the statistical power of the experiment.

Advertising 42

Advertising Testing Sales Statistics 42

datapine

AUGUST 29, 2022

He founded the project Apache Storm in 2011, which turned to be “one of the world’s most popular stream processors and has been adopted by many of the world’s largest companies, including Yahoo!, Microsoft, Alibaba, Taobao, WebMD, Spotify, Yelp” according to Marz himself.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Domino Data Lab

MARCH 3, 2019

What’s been the impact of using ML models on culture and organization? Who builds their models? We also used maturity , in other words how long had an enterprise organization been deploying ML models in production? “Three surveys of AI adoption reveal key advice from more mature practices”. Management.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Sisense

MAY 4, 2020

These statistics highlight how large the task is to extract, transform, and load data that will be ready for analysis. As long ago as 2011, the McKinsey Global Institute estimated that retailers using data analytics at scale could increase their operating margins by more than 60 percent. analytics- and data-driven) or obsolete. ”.

Big Data 78

Big Data Data-driven Snapshot Unstructured Data 78

Occam's Razor

FEBRUARY 22, 2010

Feel better? : ) When should you start doing paid search advertising for tours to Italy for 2011? For example, with Alexa , you can report on traffic statistics (such as rank and page views), upstream (where your traffic comes from) and downstream (where people go after visiting your site) statistics, and key-words driving traffic to a site.

Metrics 123

Metrics Advertising Reporting Software 123

Domino Data Lab

JULY 9, 2019

Diving into examples of building and deploying ML models at The New York Times including the descriptive topic modeling-oriented Readerscope (audience insights engine), a prediction model regarding who was likely to subscribe/cancel their subscription, as well as prescriptive example via recommendations of highly curated editorial content.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

O'Reilly on Data

MAY 21, 2019

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. For example, in a July 2018 survey that drew more than 11,000 respondents, we found strong engagement among companies: 51% stated they already had machine learning models in production.

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238

Domino Data Lab

SEPTEMBER 25, 2019

A big part of statistics, particularly for financial and econometric data, is analyzing time series, data that are autocorrelated over time. One of the most common ways of fitting time series models is to use either autoregressive (AR), moving average (MA) or both (ARMA). Chapter Introduction: Time Series and Autocorrelation.

Forecasting 87

Forecasting Modeling Statistics Optimization 87

Juice Analytics

MARCH 22, 2021

This work from 2011 was ahead of it’s time — as is most of Victor’s imaginative, inspirational work. How to Forecast an American’s Vote by The Economist “We have built a statistical model to estimate the odds of how each respondent will vote in next week’s mid-term elections.” How Many High School Stars Make It in the NBA?

Visualization 135

Visualization Interactive Statistics Forecasting 135

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

1]" Statistics, as a discipline, was largely developed in a small data world. More people than ever are using statistical analysis packages and dashboards, explicitly or more often implicitly, to develop and test hypotheses. This question is statistical or methodological in nature. Know what matters.

Experimentation 61

Experimentation Testing Statistics Metrics 61

Ontotext

MARCH 24, 2021

For these reasons, publishing the data related to elections is obligatory for all EU member states under Directive 2003/98/EC on the re-use of public sector information and the Bulgarian Central Elections Committee (CEC) has released a complete export of every election database since 2011. The road ahead.

Statistics 142

Statistics Data Processing Publishing Metrics 142

Edwin Chen

JANUARY 7, 2013

— Sohaib Athar (@ReallyVirtual) May 1, 2011. We’ll describe a novel real-time human computation engine we built that allows us to find search queries as soon as they’re trending, send these queries to real humans to be judged, and finally incorporate these human annotations into our backend models.

Statistics 73

Statistics Machine Learning Advertising Metadata 73