O'Reilly on Data

MAY 27, 2020

So the state calculates and publishes a “Risk Adjusted Mortality Ratio”—a comparison between the actual number of observed deaths and the number that would be statistically expected, on average, for patients medically similar to those each doctor actually operated on.

Testing 354

Testing Risk Reporting Measurement 354

Domino Data Lab

JANUARY 6, 2019

I’ve been teaching data science since 2008 privately for employers – exec staff, investors, IT teams, and the data teams I’ve led – and since 2013, for industry professionals in general. Also, clearly there’s no “one size fits all” educational model for data science. The Berkeley model addresses large university needs in the US.

Data Science 56

Data Science Machine Learning Visualization Reporting 56

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

Data Science and Beyond

JULY 22, 2018

Two years later, I published a post on my then-favourite definition of data science , as the intersection between software engineering and statistics. I was very comfortable with that definition, having spent my PhD years on several predictive modelling tasks, and having worked as a software engineer prior to that.

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79

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

Domino Data Lab

AUGUST 8, 2019

Meanwhile, many organizations also struggle with “late in the pipeline issues” on model deployment in production and related compliance. then building machine learning models to recommend methods and potential collaborators to scientists. 2008 – Financial crisis : scientists flee Wall St.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Occam's Razor

SEPTEMBER 29, 2009

When you are trying to break through the noise you'll take any measure of success to detect a signal, use the macro & micro conversion mental model. It shows which terms (hence brands, sites, properties) have risen the by the most statistically significant amounts. Outcome #6: To destroy your competition.

Measurement 130

Measurement Metrics Analytics Marketing 130

datapine

NOVEMBER 19, 2019

Currently, popular approaches include statistical methods, computational intelligence, and traditional symbolic AI. This feature hierarchy and the filters that model significance in the data, make it possible for the layers to learn from experience. Blockchain was invented in 2008 to serve as a ledger of the cryptocurrency bitcoin.

Technology 279

Technology Internet of Things IT IoT 279

The Unofficial Google Data Science Blog

SEPTEMBER 30, 2016

The statistics app for Google Sheets hopes to change that. Editor's note: We've mostly portrayed data science as statistical methods and analysis approaches based on big data. Introduction Statistics for Google Sheets is an add-on for Google Sheets that brings elementary statistical analysis tools to spreadsheet users.

Statistics 53

Statistics Big Data Data Science Marketing 53

Domino Data Lab

MARCH 27, 2019

Select all rows from the 2008 election. votes_2008 <- filter(presidentialElections, year == 2008). The preceding filter() statement is equivalent to extracting the rows using the following base R syntax: # Select all rows from the 2008 election. votes_2008 <- presidentialElections[presidentialElections$year == 2008, ].

Statistics 85

Statistics Data Science Visualization IT 85

O'Reilly on Data

JANUARY 25, 2021

in 2008 and continuing with Java 8 in 2014, programming languages have added higher-order functions (lambdas) and other “functional” features. Models are neither code nor data, and we don’t have adequate tools for versioning models either (though tools like MLflow are a start). Starting with Python 3.0

Machine Learning 363

Machine Learning Software Testing Technology 363

Jet Global

APRIL 5, 2021

Enterprises actively use financial modeling to guide their financial planning and strategic decision-making. Financial models offer data-driven, quantitative analysis that tells you where your company stands and where it’s heading. That being said, one model can’t do it all. What Is Financial Modeling?

Modeling 98

Modeling Forecasting Metrics Finance 98