Birst BI

AUGUST 23, 2018

Source: Gartner (April 2018). If your data science resources are strained, here is an example data scientist workflow that leverages Birst to speed up tasks throughout the application development lifecycle – data preparation, model development and testing with R integration, deployment into the business, and governance and management.

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

datapine

MARCH 16, 2023

Your Chance: Want to test modern data visualization software for free? We already discuss this topic in our misleading statistics blog post in which we provided an example of a misleading bar chart by KFC. Your Chance: Want to test modern data visualization software for free? We will discuss each of them below.

Visualization 196

Visualization KPI Cost-Benefit Dashboards 196

Domino Data Lab

JULY 17, 2021

The likelihood function measures the goodness of fit of a statistical model to a sample of data for given values of the unknown parameters. Later during verification, an i-Vector extracted from a test utterance (about 15 second long) is compared against the enrolled i-Vector via a cosine similarity score. Model Performance.

Modeling 64

Modeling Testing Machine Learning Measurement 64

O'Reilly on Data

NOVEMBER 28, 2023

Unexpected outcomes, security, safety, fairness and bias, and privacy are the biggest risks for which adopters are testing. Programmers have always developed tools that would help them do their jobs, from test frameworks to source control to integrated development environments. We’d like to see more companies test for fairness.

Enterprise 267

Enterprise Modeling Testing Reporting 267

Occam's Razor

JUNE 4, 2018

It is 2018—why are there still light gray below-the-fold add to cart buttons? I mean developing and inserting a subtle collection of gentle nudges that can help increase the conversion rate by a statistically significant amount. Such is the case with A/B testing. youarekillingme. There are numerous subtle issues as well.

Strategy 124

Strategy Cost-Benefit Testing Sales 124

The Unofficial Google Data Science Blog

APRIL 23, 2024

If $Y$ at that point is (statistically and practically) significantly better than our current operating point, and that point is deemed acceptable, we update the system parameters to this better value. e-handbook of statistical methods: Summary tables of useful fractional factorial designs , 2018 [3] Ulrike Groemping.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Domino Data Lab

AUGUST 8, 2019

2018 – Global reckoning about data governance, aka “Oops!…We Another key point: troubleshooting edge cases for models in production—which is often where ethics and data meet, as far as regulators are concerned—requires much more sophistication in statistics than most data science teams tend to have. We did it again.”.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

With those stakes and the long forecast horizon, we do not rely on a single statistical model based on historical trends. For example, we may prefer one model to generate a range, but use a second scenario-based model to “stress test” the range. A single model may also not shed light on the uncertainty range we actually face.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Domino Data Lab

OCTOBER 23, 2019

As a result, there has been a recent explosion in individual statistics that try to measure a player’s impact. You can add a Makefile command test that will run all of your notebooks by issuing. test: py.test --nbval notebooks/*.ipynb. You can see what that would look like in a Makefile in the snippet below.

Statistics 59

Statistics Machine Learning Testing Modeling 59

Smarten

SEPTEMBER 6, 2019

With true self-serve business intelligence and analytics solutions, the average business user can perform data preparation, test theories and hypotheses by prototyping on their own and share clear, objective data with others.

Analytics 51

Analytics IT Business Intelligence Testing 51

Data Science and Beyond

OCTOBER 15, 2017

Here are my thoughts from 2014 on defining data science as the intersection of software engineering and statistics , and a more recent post on defining data science in 2018. Just so we’re on the same page, what is data science? No one knows for sure. What are the hardest parts of data science?

Data Science 71

Data Science Deep Learning Machine Learning Data-driven 71

Domino Data Lab

MAY 8, 2019

2018-06-21). They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have. Agile was originally about iterating fast on a code base and its unit tests, then getting results in front of stakeholders. Challenges for Transparency ”.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Domino Data Lab

MARCH 3, 2019

O’Reilly Media published our analysis as free mini-books: The State of Machine Learning Adoption in the Enterprise (Aug 2018). I’m here mostly to provide McLuhan quotes and test the patience of our copy editors with hella Californian colloquialisms. Seriously, Ben gets credit for foresight on how to organize those surveys.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Domino Data Lab

AUGUST 22, 2019

Although it’s not perfect, [Note: These are statistical approximations, of course!] Note: A test set of 19,500 such analogies was developed by Tomas Mikolov and his colleagues in their 2013 word2vec paper. This test set is available at download.tensorflow.org/data/questions-words.txt.]. Note that the final test word in Table 11.2—ma’am—is

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

O'Reilly on Data

MAY 21, 2019

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. A catalog or a database that lists models, including when they were tested, trained, and deployed. Metadata and artifacts needed for audits.

Machine Learning 234

Machine Learning Technology Deep Learning Data Science 234

datapine

NOVEMBER 27, 2019

The demand for real-time online data analysis tools is increasing and the arrival of the IoT (Internet of Things) is also bringing an uncountable amount of data, which will promote the statistical analysis and management at the top of the priorities list. BN in 2018, it is also predicted to grow with a CAGR rate of 22.43% by reaching 2024.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

O'Reilly on Data

JUNE 16, 2020

We know, statistically, that doubling down on an 11 is a good (and common) strategy in blackjack. In the 2018 midterms, for example, they began to make forecasts such as “1 in 5 chance Democrats win control (19.1%); 4 in 5 chance Republicans keep control (80.9%),” which is careful to express the probabilistic nature of the prediction.

Uncertainty 273

Uncertainty Testing Risk Reporting 273