DataRobot Blog

OCTOBER 27, 2022

As highlighted in the DataRobot interface above, the Data Drift tab is enhanced with a Drill Down section for users to visualize drift details. You might think that overall, the model’s features drifted relatively little in production, but in reality, the model’s drift statistics might be fluctuating quite a bit up and down.

Data Science 52

Data Science Experimentation Visualization Modeling 52

Rocket-Powered Data Science

JULY 7, 2019

Computer Vision: Data Mining: Data Science: Application of scientific method to discovery from data (including Statistics, Machine Learning, data visualization, exploratory data analysis, experimentation, and more). They cannot process language inputs generally. Examples: (1) Automated manufacturing assembly line. (2)

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

Depict Data Studio

MARCH 27, 2023

About the Instructor: Stefanie Posavec According to Stefanie’s website , she is “a designer, artist, and author exploring experimental approaches to communicating data and information to all ages and audiences.” The structure really differentiates linear, predictable dashboards from exploratory, artistic visualizations.

Visualization 52

Visualization Consulting Dashboards Experimentation 52

FineReport

DECEMBER 11, 2019

. – Head First Data Analysis: A learner’s guide to big numbers, statistics, and good decisions. The big news is that we no longer need to be proficient in math or statistics, or even rely on expensive modeling software to analyze customers. By Michael Milton. – Data Divination: Big Data Strategies.

Big Data 98

Big Data Statistics Experimentation Data Strategy 98

Octopai

MAY 2, 2022

Your dashboards, charts, visualizations… they’re all products. . Common elements of DataOps strategies include: Collaboration between data managers, developers and consumers A development environment conducive to experimentation Rapid deployment and iteration Automated testing Very low error rates. Issue detected?

Manufacturing 87

Manufacturing Testing Experimentation Data Quality 87

FineReport

DECEMBER 19, 2019

At the same time, it also advocates visual exploratory analysis. The visualization component library of FineReport is very rich. In addition, Jupyter Notebook is also an excellent interactive tool for data analysis and provides a convenient experimental platform for beginners. It can produce a variety of complex reports.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

Octopai

OCTOBER 26, 2022

When DataOps principles are implemented within an organization, you see an increase in collaboration, experimentation, deployment speed and data quality. Continuous pipeline monitoring with SPC (statistical process control). What DataOps best practices put you on track to achieving this ideal? Let’s take a look. Results (i.e.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

DataRobot

JANUARY 13, 2022

Data scientists typically come equipped with skills in three key areas: mathematics and statistics, data science methods, and domain expertise. It offers a visual and intuitive UI that enables anyone to explore and prepare data for machine learning, no matter their previous machine-learning experience.

ROI 52

ROI Machine Learning Experimentation Data Science 52

Smarten

MAY 11, 2017

The Smarten Advanced Data Discovery gives users the freedom to leverage data beyond simple visual data analysis and dashboards. Advanced Data Discovery ensures data democratization by enabling users to drastically reduce the time and cost of analysis and experimentation.

Experimentation 49

Experimentation Visualization Business Intelligence Predictive Analytics 49

CIO Business Intelligence

JUNE 28, 2023

As Belcorp considered the difficulties it faced, the R&D division noted it could significantly expedite time-to-market and increase productivity in its product development process if it could shorten the timeframes of the experimental and testing phases in the R&D labs.

Digital Transformation 78

Digital Transformation Cost-Benefit Informatics Data mining 78

Smarten

JULY 3, 2017

When an enterprise selects a self-serve business intelligence solution with Advanced Data Discovery , Smart Data Visualization , Plug n’ Play Predictive Analysis and Self-Serve Data Preparation , it can create an environment where business users are empowered and become greater assets to the organization. It’s simple!

Predictive Modeling 40

Predictive Modeling Visualization Business Intelligence Experimentation 40

IBM Big Data Hub

APRIL 18, 2024

LLMs like ChatGPT are trained on massive amounts of text data, allowing them to recognize patterns and statistical relationships within language. Instead of a dry lecture, it presents the concept visually with interactive simulations and breaks it down into smaller, more manageable steps.

Cost-Benefit 90

Cost-Benefit Modeling Manufacturing Interactive 90

Domino Data Lab

DECEMBER 4, 2020

Domino Lab supports both interactive and batch experimentation with all popular IDEs and notebooks (Jupyter, RStudio, SAS, Zeppelin, etc.). We can group by study arm and calculate various statistics as mean and standard deviation. In this tutorial we will use JupyterLab. pain_df.TIME.== 0, pain_df.DOSE, missing).

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

O'Reilly on Data

APRIL 19, 2021

We’ll look at this later, but being able to reproduce experimental results is critical to any science, and it’s a well-known problem in AI. When asked which tools they planned to incorporate over the coming 12 months, roughly half of the respondents answered model monitoring (57%) and model visualization (49%). Maturity by Continent.

Enterprise 353

Enterprise Modeling Risk Manufacturing 353

The Unofficial Google Data Science Blog

JANUARY 16, 2018

Experimentation on networks A/B testing is a standard method of measuring the effect of changes by randomizing samples into different treatment groups. However, the downside of using a larger unit of randomization is that we lose experimental power. Figure 4 is a visual representation of these steps.

Testing 58

Testing Experimentation Measurement Modeling 58

Cloudera

NOVEMBER 25, 2020

How can he make it easy to see statistics, and do calculations, on discovered commonalities, across structured and unstructured data? An integrated, out of the box visualization and dashboard service that is integrated across multiple compute options, to expedite cross-organization collaboration with a consistent visual language.

Data Warehouse 58

Data Warehouse Unstructured Data Analytics Visualization 58

Domino Data Lab

MAY 8, 2019

On the other hand, as Lipton emphasized, while the tooling produces interesting visualizations, visualizations do not imply interpretation. ML model interpretability and data visualization. From my experiences leading data teams, when a business is facing difficult challenges, data visualizations can help or hurt.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Occam's Razor

AUGUST 22, 2011

Six Data Visualizations That Rock! The Awesome Power of Visualization 2 -> Death and Taxes 2007. The Awesome Power of Data Visualization. Build A Great Web Experimentation & Testing Program. Experimentation and Testing: A Primer. Tip #9: Leverage Statistical Control Limits. Web Analytics Demystified.

KPI 124

KPI Metrics Measurement ROI 124

The Unofficial Google Data Science Blog

MARCH 22, 2018

But what if users don't immediately uptake the new experimental version? Background At Google, experimentation is an invaluable tool for making decisions and inference about new products and features. by DANIEL PERCIVAL Randomized experiments are invaluable in making product decisions, including on mobile apps.

Experimentation 62

Experimentation Measurement Modeling Statistics 62

Alation

SEPTEMBER 28, 2022

Alation provides robust DataOps solutions that help you foster collaboration, build trusted data solutions, automate testing & monitoring, and visualize data pipelines. Technical environments and IDEs must be disposable so that experimental costs can be kept to a minimum. What Are The Principles of DataOps? Disposable environments.

Cost-Benefit 52

Cost-Benefit Data Quality Manufacturing Testing 52

Domino Data Lab

JUNE 23, 2019

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. You need to have these windows into the data and into your models and be able to test and change them visually.

Management 110

Management Machine Learning Experimentation Metrics 110

Occam's Razor

SEPTEMBER 13, 2016

With that as context, you can imagine how heart-broken I was when Jane shared the following visual from a study done by Econsultancy and Lynchpin. Visual perception of information. Ability to create insightful data visualizations. Hypothesis development and design of experimentation. Interpreting mathematical information.

Modeling 127

Modeling Reporting Strategy Consulting 127

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

It is important to make clear distinctions among each of these, and to advance the state of knowledge through concerted observation, modeling and experimentation. Note also that this account does not involve ambiguity due to statistical uncertainty. We sliced and diced the experimental data in many many ways.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45

Insight

MARCH 12, 2020

The most powerful approach for the first task is to use a ‘language model’ (LM), i.e. a statistical model of natural language. After some experimentation, I landed on a strategy I’ll call ‘warm encoding’: if greater than 1% of tags were in a particular class, I encoded the book as belonging to that class, non-exclusively.

Modeling 59

Modeling Metadata Publishing Sales 59

Occam's Razor

JULY 24, 2018

I’ve intended to create a simple visual that absorbs the scale, complexity and many moving parts. I wanted to create a visual that would function as a diagnostic tool to determine if you are lost, trapped in a silo or wandering aimlessly. Ignore the metrics produced as an experimental exercise nine months ago.

Analytics 93

Analytics Metrics Strategy Measurement 93

Domino Data Lab

AUGUST 22, 2019

Although it’s not perfect, [Note: These are statistical approximations, of course!] Human brains are not well suited to visualizing anything in greater than three dimensions. Visualizing data using t-SNE. Example 11.6 Detecting collocated bigrams with more conservative thresholds. Plotting Word Vectors. Example 11.9

Deep Learning 111

Deep Learning Modeling Metrics Testing 111