The Unofficial Google Data Science Blog

OCTOBER 7, 2015

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. We describe experiment designs which have proven effective for us and discuss the subtleties of trying to generalize the results via modeling.

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

IBM Big Data Hub

AUGUST 11, 2023

Because ML is becoming more integrated into daily business operations, data science teams are looking for faster, more efficient ways to manage ML initiatives, increase model accuracy and gain deeper insights. It advances the scalability of ML in real-world applications by using algorithms to improve model performance and reproducibility.

Data Science 53

Data Science Machine Learning Cost-Benefit Deep Learning 53

AWS Big Data

JULY 26, 2023

The vector engine supports the popular distance metrics such as Euclidean, cosine similarity, and dot product, and can accommodate 16,000 dimensions, making it well-suited to support a wide range of foundational and other AI/ML models. Carl has been with Amazon Elasticsearch Service since before it was launched in 2015.

Metadata 52

Metadata Cost-Benefit Testing Metrics 52

AWS Big Data

JULY 28, 2023

This query is fairly complex: it involves multiple joins and requires special knowledge of the correct way to calculate profit metrics that other end-users may not possess. Next, we take our data mesh a step further by using federated views in a multi-user model. For the data source name, use shared_federated_catalog.

Big Data 80

Big Data Data Architecture Data Lake Interactive 80

DataRobot Blog

DECEMBER 7, 2019

Using the DataRobot’s automated machine learning platform and data from numerous sources ranging from MLB payrolls, to free agent signings, to historical player performance, we built an array of AI models to tell us specific details about how this free agent market would play out, showing contract values, terms, and destinations for every player.

Machine Learning 52

Machine Learning Forecasting Metrics Modeling 52

Insight

NOVEMBER 5, 2019

Such a model would be able to answer the difficult questions above. Collected over two years (2014 and 2015) from ICUs across the US, it contains an enormous amount of data about more than 200,000 patient-stays in the ICU. In order to combine the two models, I popped the last layer off of each model and concatenated the outputs.

Deep Learning 61

Deep Learning Modeling Insurance Metrics 61

Domino Data Lab

SEPTEMBER 9, 2019

We have configured the default Compute Environment in Domino to include all of the packages, libraries, models, and data you’ll need for this tutorial. That nlp variable is now your gateway to all things spaCy and loaded with the en_core_web_sm small model for English. Getting Started. for a, b in pairs:?. print(a, b, lic[a].similarity(lic[b])).

Deep Learning 110

Deep Learning Machine Learning Data Science Visualization 110

Insight

JUNE 10, 2019

Photo by Wayne Chan on Unsplash The race to the future I don’t know about you, but I distinctly remember a promise from 1989 that flying cars would be commonplace by 2015. Transfer learning applied to ResNet50 CNN Training results The final accuracy of the model, when tested on a subset of the training data, was 97%.

Breakeven 69

Breakeven Modeling Testing Marketing 69

datapine

MARCH 31, 2022

The Bureau of Labor Statistics also states that in 2015, the annual median salary for BI analysts was $81,320. While analysts focus on historical data to understand current business performance, scientists focus more on data modeling and prescriptive analysis. This beats projections for almost all other occupations.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

AWS Big Data

FEBRUARY 1, 2023

Storage and redundancy – Due to the heterogeneous data stores and models, it was challenging to store the different datasets from various business stakeholder teams. AWS Glue Data Catalog The Data Catalog helped us maintain the catalog as an index to the data’s location, schema, and runtime metrics in Amazon S3.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Occam's Razor

MARCH 25, 2014

In a world of infinite choice, the ability to pick critical few metrics to focus on is, well…, critical. In this post I want to share that one-page list of the best metrics for digital content, marketing and business success with you. Best Digital Metrics: Own Existences/Strategies. It would not surprise me.

Metrics 155

Metrics Marketing Strategy Key Performance Indicator 155

The Unofficial Google Data Science Blog

MAY 31, 2016

This means it is possible to specify exactly in which geos an ad campaign will be served – and to observe the ad spend and the response metric at the geo level. In other words, iROAS is the slope of a curve of the response metric plotted against the underlying advertising spend. They are non-overlapping geo-targetable regions.

Advertising 42

Advertising Testing Sales Statistics 42

Occam's Razor

SEPTEMBER 15, 2014

They will need two different implementations, it is quite likely that you will end up with two sets of metrics (more people focused for mobile apps, more visit focused for sites). Media-Mix Modeling/Experimentation. Mobile content consumption, behavior along key metrics (time, bounces etc.) And again, a custom set of metrics.

Metrics 141

Metrics Reporting Analytics Marketing 141

Andrew White

JANUARY 9, 2022

A data fabric has the same model but it adds a set of capabilities that continuously monitor the whole landscape, and continuously update the intelligent part that infers insight as new data is discovered and/or added. I would suggest that one way to explore it is to explore the idea of a standard operating model.

Analytics 64

Analytics Measurement Modeling Data-driven 64

The Unofficial Google Data Science Blog

JUNE 30, 2016

The choice of space $cal F$ (sometimes called the model ) and loss function $L$ explicitly defines the estimation problem. In the presence of model misspecification, the estimator $hatpsi$ is inconsistent. As a result, estimators that focus on covariate balancing are also susceptible to being inconsistent due to model misspecification.

Statistics 44

Statistics Optimization Modeling Experimentation 44

Occam's Razor

JANUARY 9, 2012

If you are doing lame stuff, why try harder in an analytics context by asking for Economic Value or Visitor Loyalty or Conversation Rate or a thousand other super powerful and insightful metrics ? Our mental model has not shifted enough to the existing reality. Fill it with the best web metrics to measure success. Got your own?

Marketing 140

Marketing B2B Measurement Risk 140

IBM Big Data Hub

NOVEMBER 13, 2023

In 2015, Google donated Kubernetes as a seed technology to the Cloud Native Computing Foundation (CNCF) (link resides outside ibm.com), the open-source, vendor-neutral hub of cloud-native computing. This mitigates potential issues like traffic surges, hardware problems or network disruptions.

Machine Learning 108

Machine Learning Data-driven Software Testing 108

Domino Data Lab

FEBRUARY 4, 2019

Lately there’s been lots of dialog about bias in machine learning models, though considering the noise part of the equation is an important corollary. Problems with training ML models efficiently. I don’t have a metric to estimate the time it takes to change company culture because that’s what we call a very small dataset.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

IBM Big Data Hub

FEBRUARY 2, 2024

What companies are doing : Companies are incorporating sustainable practices into their business models. It often entails efforts like fair trade practices, investing in local economies, ensuring safe working conditions and adherence to ESG (Environmental, Social, and Governance) metrics.

Optimization 85

Optimization Cost-Benefit Strategy Technology 85

IBM Big Data Hub

FEBRUARY 22, 2024

Earning trust in the outputs of AI models is a sociotechnical challenge that requires a sociotechnical solution. There must be a concerted effort to make these principles a reality through consideration of the functional and non-functional requirements in the models and the governance systems around those models.

Metadata 92

Metadata Measurement Risk Modeling 92

Sisense

FEBRUARY 24, 2021

But that number rose sharply afterwards, with the team noting there were over 1,000 people in this role by 2015. Challenge: CDOs are looking for an analytics solution that is flexible enough for the highly technical modeling that data analysts and engineers need while also being accessible for the business analyst.

Data Warehouse 69

Data Warehouse Big Data Metrics Visualization 69

Alation

FEBRUARY 20, 2020

Following the trail of usage… Some catalogs may try to be a source-of-truth for the right table to consult for a given purpose, the right categorization of a given value, or the right way to calculate a given metric. If I see a metric in a report, I want to be able to look it up, even if it shouldn’t have been used in the first place.

Metrics 52

Metrics Consulting Machine Learning Statistics 52

CIO Business Intelligence

MAY 17, 2022

The company is on a mission to revolutionize the banking industry through technology and data and serves as a model for harnessing the power of data for growth. . Around 2015, Capital One went to AWS re:Invent and set forth our aspirational goal to modernize our entire technology infrastructure.

ROI 52

ROI Risk Marketing Modeling 52

CIO Business Intelligence

AUGUST 12, 2022

in 2013, Alfa Aesar in 2015, Affymetrix and FEI Co. We’re very much focused on the commercialization of acquisitions, making sure we don’t break the deal models and that things are running as they should be,” says John Stevens, vice president of IT at Thermo Fisher. in 2016, and BD Advanced Bioprocessing in 2018. Catalyzing change.

IT 105

IT Data Lake Sales Interactive 105

Jet Global

SEPTEMBER 8, 2020

In July of 2015, over nine years after its initial launch, New Horizons completed its successful fly-by exploration of Pluto. xP&A enables business leaders to consolidate forecasts and performance metrics from across the entire organization. Instead, they planned for periodic adjustments to correct the spacecraft’s course.

Finance 64

Finance Forecasting Sales Enterprise 64

Occam's Razor

JULY 22, 2013

My solution to these problems was to create a simple framework we can use to put our customers first, evaluate our marketing programs, and right-align our view of success (metrics). What about grabbing the incredible mobile opportunity by the throat and truly delivering for utility marketing and executing for mobile 2015 ?

Measurement 163

Measurement Marketing Key Performance Indicator Metrics 163

Sisense

MARCH 18, 2019

My involvement with Sisense started in mid-2015. As part of our continuing tech investments, CTSI-Global decided to incorporate modern BI technology to help shippers perform advanced forecasting and modeling through elegant and robust visualizations on top of the centralized shipping data we aggregate. Automation and Integration.

Analytics 71

Analytics Dashboards Metrics Visualization 71

Jet Global

JANUARY 20, 2021

In July of 2015, over nine years after its initial launch, New Horizons completed its successful fly-by exploration of Pluto. xP&A enables business leaders to consolidate forecasts and performance metrics from across the entire organization. Instead, they planned for periodic adjustments to correct the spacecraft’s course.

Finance 52

Finance Metrics Key Performance Indicator Reporting 52

Smart Data Collective

JUNE 26, 2019

Get Rid of Blind Spots in Statistical Models With Machine Learning. Data-related blind spots could also exist in your statistical models. RiskSpan is a company that built a machine learning algorithm that can flag error-prone parts of a statistical model and indicate which associated outputs may be unreliable.

ROI 103

ROI Statistics Machine Learning Measurement 103

CIO Business Intelligence

JUNE 5, 2024

In 2015, Major League Baseball revolutionized a sport already known for its sophisticated use of data with MLB Statcast, a tracking technology that collects enormous amounts of game data. Not only do we have the traditional ball tracking metrics like velocity and spin rate, we’ve also got player positioning data,” Booth says.

Optimization 97

Optimization Predictive Modeling Data-driven Modeling 97

Occam's Razor

FEBRUARY 9, 2015

. + Traffic Trends Key Metrics Analysis. Onsite Behavior Key Metrics Analysis. I tend to use Hitwise a lot less, or not at all, because it is a very hard to use, it is slow, the UX/UI, metrics and reports have not really evolved over the years. Traffic Trends Key Metrics Analysis. It is 2015. Is it someone else?

Metrics 155

Metrics Reporting IT Advertising 155

Occam's Razor

JULY 13, 2017

5: What-if Analysis Models. Oh, or your main traffic sources and the visitor acquisition metrics? allow for smart elements like modeling. Strategy 5: What-if Analysis Models. Why not build in a model where the decision maker can change Conversion Rates, to see the impact on Revenue? 2: If Complex, Focus!

Visualization 124

Visualization Strategy Interactive Statistics 124