Domino Data Lab

AUGUST 5, 2019

This Domino Data Science Field Note covers Chris Wiggins ‘s recent data ethics seminar at Berkeley. He also encouraged data scientists to understand how new data science algorithms rearrange power as well as how the history of data is a story of truth and power.

Data Science 93

Data Science Data-driven Modeling Machine Learning 93

Jen Stirrup

SEPTEMBER 25, 2020

Certainly, if you take a look at some of the discussion on social media, it doesn’t take long to see that the SQL Family / Data Platform discussions online have become very heated. From my first SQLBits session in 2010, I have spent the last decade speaking all over the world. Get in touch and I can help.

Data Science 93

Data Science IT 93

Domino Data Lab

SEPTEMBER 18, 2019

Models are at the heart of data science. Data exploration is vital to model development and is particularly important at the start of any data science project. Do you know of any good data sets to explore? This data will be explored with a Jupyter Notebook [and Domino project]. Introduction.

Visualization 99

Visualization Interactive Machine Learning Data Science 99

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. Introduction Time series data appear in a surprising number of applications, ranging from business, to the physical and social sciences, to health, medicine, and engineering. by STEVEN L.

Forecasting 64

Forecasting Statistics Modeling Software 64

Domino Data Lab

APRIL 3, 2019

This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form. Rinse, lather, repeat. Those are table stakes in this game.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Peter James Thomas

JUNE 20, 2019

The above chart compares monthly searches for Business Process Reengineering (including its arguable rebranding as Business Transformation ) and monthly searches for Data Science between 2004 and 2019. Here we come back to the upward trend in searches for Data Science. Source: Google Trends. Reengineering Redux.

Cost-Benefit 55

Cost-Benefit Data Warehouse Consulting Data Science 55

Timo Elliott

JANUARY 10, 2022

I’m an innovation evangelist for SAP. It’s a little bit of a strange title, but it basically means I work with our customers on the leading edge of innovation, try and gather the lessons learned and then share that with as many people as possible so that we can all be more successful. I have exactly the same one!

Data Processing 121

Data Processing Manufacturing Machine Learning Technology 121

Domino Data Lab

DECEMBER 2, 2020

Compared to centroid-based clustering like k-means, density-based clustering works by identifying “dense” clusters of points, allowing it to learn clusters of arbitrary shape and identify outliers in the data. neighborhoods is given a data point, we want to be able to reason about the data points in the space around it.

Metrics 116

Metrics KDD Testing Machine Learning 116

The Unofficial Google Data Science Blog

JULY 22, 2020

However, if one changes assignment weights when there are time-based confounders, then ignoring this complexity can lead to biased inference in an OCE. In the case of MABs, ignoring this complexity can also lead to poor total reward, making it counterproductive towards its intended purpose.

Experimentation 95

Experimentation Statistics Testing Strategy 95

Edwin Chen

SEPTEMBER 29, 2011

Data Science 0.328. Inception (2010 movie) 0.535. The Social Network (2010 movie) 0.513. Caltech students are interested in Computer Science , MIT hackers are interested in Computer Security , and Stanford students are interested in Human-Computer Interaction. UX Design 0.337. Web Application Frameworks 0.336.

Finance 81

Finance Interactive Machine Learning Advertising 81

The Unofficial Google Data Science Blog

AUGUST 27, 2019

As we note, uniform sampling is unlikely to get enough positive samples to draw inference about the proportion. But importance sampling in statistics is a variance reduction technique to improve the inference of the rate of rare events, and it seems natural to apply it to our prevalence estimation problem.

Metrics 98

Metrics Statistics Uncertainty Optimization 98

O'Reilly on Data

SEPTEMBER 19, 2023

” They weren’t quite sure what this “data” substance was, but they’d convinced themselves that they had tons of it that they could monetize. In short order, it was tough to get a data job if you didn’t have some Hadoop behind your name. Cloud computing? And Hadoop rolled in. Until it wasn’t.

Machine Learning 246

Machine Learning Testing Modeling Cost-Benefit 246

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

Yet when we use these tools to explore data and look for anomalies or interesting features, we are implicitly formulating and testing hypotheses after we have observed the outcomes. We ought not dredge our data. For better and for worse, technology has led to a democratization of data within organizations. Is it actionable?

Experimentation 61

Experimentation Testing Statistics Metrics 61

The Unofficial Google Data Science Blog

MARCH 31, 2016

Random effects can be viewed as an application of empirical Bayes, and if we broaden our view to that parent technique, we can find theoretical evidence of their superiority over say fixed effects models. These predictive posterior distributions have many uses such as in multi-armed bandit problems. See [9], [10] for a discussion of this approach.

Modeling 40

Modeling Statistics Advertising Testing 40

O'Reilly on Data

MARCH 20, 2019

It’s also possible a malicious external actor could acquire unauthorized access to some or all of your training data and poison it. A very direct kind of data poisoning attack might involve altering the labels of a training data set. It seems entirely possible to do the same with customer or transactional data.

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

Cloudera

APRIL 21, 2022

MHS Genesis has to tackle an almost impossible job in moving and processing petabytes of data, securely and accurately. A key reason for selecting Cerner, the DoD said , was the company’s data center allows direct access to proprietary data that it couldn’t obtain from a government-hosted environment. The core of the EHR system.

Metadata 90

Metadata Informatics Insurance Data Processing 90

O'Reilly on Data

JANUARY 25, 2021

Search data is distorted by how quickly customers find what they want: if they don’t succeed, they may try a similar search with many of the same terms. We haven’t combined data from multiple terms. While we can’t compare in-person conference data with virtual event data, we can make a few observations.

Machine Learning 363

Machine Learning Software Testing Technology 363

datapine

APRIL 16, 2019

The term ‘big data’ alone has become something of a buzzword in recent times – and for good reason. Fundamentally, data driven decision making means working towards key business goals by leveraging verified, analyzed data rather than merely shooting in the dark. Why Data Driven Decision Making Is Important?

Data-driven 287

Data-driven Dashboards Visualization Cost-Benefit 287