O'Reilly on Data

APRIL 19, 2021

In contrast, in our 2018 report, Asia was behind in mature practices, though it had a markedly higher number of respondents in the “early adopter” or “exploring” stages. 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%).

Enterprise 356

Enterprise Modeling Risk Manufacturing 356

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

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. He also really informed a lot of the early thinking about data visualization. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. It’s also a driver for data science.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

MAY 8, 2019

2018-06-21). On the other hand, as Lipton emphasized, while the tooling produces interesting visualizations, visualizations do not imply interpretation. ML model interpretability and data visualization. Business stakeholders cannot rely on visualizations to interpret the ML models that their data science teams produce.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

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. The describe function on a Pandas DataFrame provides descriptive statistics, including the number of columns, in this case 27, and median (this is the 50 percent row), for each column. 05) in predicting changes in attendance.

Statistics 59

Statistics Machine Learning Testing Modeling 59

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). What metrics are used to evaluate success? Note how model visualization is bubbling up to the top, which has implications for model interpretability, cyber threats, etc. Who builds their models?

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!] 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 0.85 = 0.15.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

datapine

NOVEMBER 27, 2019

Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2) Data Discovery/Visualization. Data exploded and became big.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361