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. Daily Interactions. Technical environments and IDEs must be disposable so that experimental costs can be kept to a minimum. It’s a Team Sport. Self-Organize.

Cost-Benefit 52

Cost-Benefit Data Quality Manufacturing Testing 52

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

Cloudera

NOVEMBER 25, 2020

Scale to provide 1,000s of researchers frictionless interaction with data. How can he make it easy to see statistics, and do calculations, on discovered commonalities, across structured and unstructured data? How can users drill down, in non-technical ways, to quickly interact with data that explains what correlations seem to matter?

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

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. Yet, this challenge is not insurmountable. for what is and isn’t possible) to address these challenges.

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

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

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. These quasi-explanations usually involve large, real effects and interactions so complex that arguments based on them are often non-falsifiable.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45

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. Interactive bokeh plot of two-dimensional word-vector data. produces the interactive scatterplot in Figure 11.9

Deep Learning 111

Deep Learning Modeling Metrics Testing 111