Sisense

JULY 10, 2019

As of 2017, Linux was running 90% of the public cloud workload. Given this importance, we made it an organizational priority to invest in a Sisense on Linux deployment in late 2017. When I was tasked with the responsibility of building a Sisense Linux deployment in late 2017, a few small steps had already been taken.

IT 69

IT Testing Technology Sales 69

Smarten

NOVEMBER 22, 2017

These tools allow the enterprise to establish and monitor key metrics and to objectively assess results. With the power to test competitive and market strategies, management and business users can see and leverage the hidden value within the organization and find the small problems before they become large issues.

Analytics 40

Analytics IT Business Intelligence Visualization 40

Data Science 101

MAY 6, 2019

This was released as MBUX in 2017 and that was a pretty cool project because there were a lot of challenges that you wouldn’t normally have to solve if you had access to a massive data set or connectivity. We pulled questions from some of our Springboard students and this one is from Miguel, who is in our data science vertical.

Data Science 98

Data Science Modeling Machine Learning Testing 98

Insight

OCTOBER 25, 2019

This category was not considered for the purpose of this project as it does not allow for a 3-way partition for disjoint training, validation, and testing sets. My client also specified that CAD model files of the T-LESS dataset be used for this project, and that one object per class be reserved for testing (Objects 4, 8, 12, 18, 23, 30).

Snapshot 57

Snapshot Testing Deep Learning Visualization 57

O'Reilly on Data

JUNE 19, 2019

In a previous post , we noted some key attributes that distinguish a machine learning project: Unlike traditional software where the goal is to meet a functional specification, in ML the goal is to optimize a metric. A catalog or a database that lists models, including when they were tested, trained, and deployed.

Modeling 194

Modeling Machine Learning Testing Metrics 194

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). Mobile content consumption, behavior along key metrics (time, bounces etc.) If you have ecommerce you will see key metrics related to money making.

Metrics 141

Metrics Reporting Analytics Marketing 141

The Unofficial Google Data Science Blog

APRIL 23, 2024

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

datapine

MAY 11, 2022

Therefore, the visualization of data is critical to the sustained success of your business and to help you yield the most possible value from this tried and tested means of analyzing and presenting vital information. Retail analytics tools allow you to visualize relevant metrics in interactive bar charts such as the one displayed below.

Visualization 252

Visualization Dashboards Key Performance Indicator Sales 252

Domino Data Lab

MAY 20, 2021

Working with highly imbalanced data can be problematic in several aspects: Distorted performance metrics — In a highly imbalanced dataset, say a binary dataset with a class ratio of 98:2, an algorithm that always predicts the majority class and completely ignores the minority class will still be 98% correct. return synthetic. Chawla et al.,

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Depict Data Studio

SEPTEMBER 13, 2023

Grant Deliverables In this blog post , you’ll see how Josephine Engels did need to start from scratch — she was visualizing these metrics for her organization for the first time — and then made several dashboards to track grant deliverables. Adapt one of these dashboards instead. Learn how inside Dashboard Design.

Dashboards 52

Dashboards Visualization Snapshot Data-driven 52

Domino Data Lab

MAY 8, 2019

Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. Adrian Weller (2017-07-29). “ If your “performance” metrics are focused on predictive power, then you’ll probably end up with more complex models, and consequently less interpretable ones. Challenges for Transparency ”. 2018-06-21).

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

The Unofficial Google Data Science Blog

JULY 18, 2023

Once we’ve answered that, we will then define and use metrics to understand the quality of human-labeled data, along with a measurement framework that we call Cross-replication Reliability or xRR. We will follow the example of Janson and Olsson , and start from this generalized definition of the metric, which they call iota.

Measurement 52

Measurement Metrics Uncertainty Slice and Dice 52

Cloudera

MAY 18, 2021

Value-at-Risk (VaR) is a widely used metric in risk management. It helps identify risk exposures, informs pre-trade decisions, and is reported to regulators for stress testing. 2] Bayraktar, Erhan and Munk, Alexander, Mini-Flash Crashes, Model Risk, and Optimal Execution (May 27, 2017). Intraday VaR. Citations. [1]

Risk 92

Risk Marketing Risk Management Data-driven 92

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

For example, consider the following simple example fitting a two-dimensional function to predict if someone will pass the bar exam based just on their GPA (grades) and LSAT (a standardized test) using the public dataset (Wightman, 1998). Curiosities and anomalies in your training and testing data become genuine and sustained loss patterns.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Insight

MARCH 25, 2019

Bugs in a third-party CDN provider’s system, such as this one from 2017, can have serious implications for the security and privacy of your users. I incorporated ExternalDNS into kubeCDN and configured my video test service to use ExternalDNS and set a DNS record when deployed.

Data Processing 106

Data Processing Cost-Benefit Optimization Metrics 106

Occam's Razor

JANUARY 8, 2018

If you are a reader of my newsletter, The Marketing < > Analytics Intersect , you’ve seen me apply it to metrics (last TMAI was on Bounce Rate), reports, frameworks and more. In 2017, they've twice replaced the company's Chief Revenue Officer. Had it been tested? Condé Nast | A Story of Unrequited Love.

Sales 133

Sales Predictive Analytics Insurance Data Warehouse 133

Domino Data Lab

OCTOBER 23, 2019

Knowing that the ultimate goal is to compare the social-media influence and power of NBA players, a great place to start is with the roster of the NBA players in the 2016–2017 season. You can add a Makefile command test that will run all of your notebooks by issuing. test: py.test --nbval notebooks/*.ipynb. 35,vjust=1).

Statistics 59

Statistics Machine Learning Testing Modeling 59

Domino Data Lab

AUGUST 1, 2021

Because of its architecture, intrinsically explainable ANNs can be optimised not just on its prediction performance, but also on its explainability metric. After forming the X and y variables, we split the data into training and test sets. For sample 23 from the test set, the model is leaning towards a bad credit prediction.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Occam's Razor

DECEMBER 8, 2017

If the Surface Marketing team is like every other team at every other company engaged in sponsorships and television advertising, it’ll measure the same collection of smart metrics like everyone else. Better than Reach and Brand Lift metrics? As the season went on, we could look for test and control opportunities.

Broadcasting 121

Broadcasting Measurement Marketing Sales 121

datapine

NOVEMBER 27, 2019

Another increasing factor in the future of business intelligence is testing AI in a duel. Augmented analytics can identify meaningful relationships between certain metrics and various other business variables, generate a dashboard and present the data story in a simple, non-technical manner. BN by 2023, with a CAGR of 13.6%

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

O'Reilly on Data

JANUARY 25, 2021

Both SRE and DevOps emphasize similar practices: version control (62% growth for GitHub, and 48% for Git), testing (high usage, though no year-over-year growth), continuous deployment (down 20%), monitoring (up 9%), and observability (up 128%). It’s particularly difficult if testing includes issues like fairness and bias.

Machine Learning 363

Machine Learning Software Testing Technology 363

Alation

AUGUST 26, 2021

HBR Review May/June 2017. A common BI application is the BI dashboard, which displays key metrics so that leaders have a “big picture view” to inform wise goals and decisions. Next, you test these use cases with the software chosen. Field Test Use Cases. Source: “What’s Your Data Strategy?” Data Intelligence and Metadata.

Metadata 64

Metadata Data Governance Dashboards Software 64