Data Science 101

MAY 6, 2019

I think in physics one of the things that attracted me most to the field that I studied, which was particle physics, was the ability to leverage computer science mathematical modeling and data visualization to solve big questions. If the recruiter feels like that’s unnecessary, they may move you directly to an onsite. it’s not cheating.

Data Science 98

Data Science Modeling Machine Learning Testing 98

Insight

OCTOBER 25, 2019

Three views for Object 12: CAD model as visualized by Microsoft’s Print 3D software (left). Pipeline 1: Data Augmentation + Bag of Visual Words The first pipeline is relatively straightforward and can be considered our benchmark for performance. Model performance is evaluated on aggregated metrics of individual tasks.

Snapshot 57

Snapshot Testing Deep Learning Visualization 57

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.

Dashboards 52

Dashboards Visualization Snapshot Data-driven 52

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

MAY 8, 2019

Finale Doshi-Velez, Been Kim (2017-02-28) ; see also the Domino blog article about TCAV. Adrian Weller (2017-07-29). “ On the other hand, as Lipton emphasized, while the tooling produces interesting visualizations, visualizations do not imply interpretation. ML model interpretability and data visualization.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Rita Sallam

NOVEMBER 11, 2016

The vision revealed in the keynote had an unmistakable emphasis on the enterprise, but as the market for visual-based data discovery is mainstreaming, Tableau also laid a foundation for building a next generation, ‘smart’ BIA platform. What’s on Deck for 2017? This new engine will replace the.TDE by end of 2017. Time will tell.

Visualization 49

Visualization Metrics Machine Learning Enterprise 49

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.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Smarten

JANUARY 7, 2020

Every business understands the value of objective metrics and accurate analysis and the modern BI environment is designed to support these goals at every level of the organization. How is Modern BI Different From Traditional BI?

IT 52

IT Business Intelligence ROI Reporting 52

Sisense

MARCH 25, 2020

According to a 2017 survey that polled 1,000 professional software developers from the United States and Great Britain, 41% of respondents cited “waiting for other people to do stuff” and “meetings where I mostly remain silent” (40%), as their biggest time-wasters. Overcoming workplace time-sucks.

Dashboards 75

Dashboards Visualization Reporting Management 75

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

As a result, selecting knots according to the quantiles of the input data (or even linearly across the domain), and then steadily increasing their number as long as the metrics improve works well in practice. More knots make the learned feature transformation smoother and more capable of approximating any monotonic function. Pfeifer, J.

Machine Learning 108

Machine Learning Deep Learning Modeling Interactive 108

Jet Global

MAY 27, 2021

However, fear of the unknown has left many companies afraid to implement a new reporting tool, yet the risk of staying with Discoverer increases day by day: Discoverer extended support ended June 2017. Reporting and visual analysis. Hubble delivers significant benefits to the team, helping us understand key spend metrics.”.

Reporting 52

Reporting Cost-Benefit Dashboards Finance 52

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. One of the things this data set doesn’t have, however, is a single metric to rank both offensive and defensive performance in a single statistic.

Statistics 59

Statistics Machine Learning Testing Modeling 59

Domino Data Lab

FEBRUARY 4, 2019

People who attended JupyterCon 2017–2018 can attest, an “industry poster session” includes an open bar, catered hors d’oeuvres, lots of mingling … to paraphrase feedback from JupyterCon, “As a tech person, would I get up extra early to meet strangers for coffee at 8:00 am? I double-dare you not to visualize that cohort!

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Business Over Broadway

DECEMBER 20, 2018

Data Science/Analytics Tools, Technologies and Languages used in 2017. A recent survey by Kaggle revealed that data professionals used data visualization, logistic regression, cross-validation and decision trees more than other data science methods in 2017. Data Science/Analytics Tools, Technologies and Languages used in 2017.

Machine Learning 74

Machine Learning Data Science Deep Learning Predictive Analytics 74

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. Skater provides a wide range of algorithms that can be used for visual interpretation (e.g. Courville, Pascal Vincent, Visualizing Higher-Layer Features of a Deep Network, 2009.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

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

Occam's Razor

JULY 13, 2017

In service of that belief, there are few things that bring me as much joy as visualizing data (smart segmentation comes close). While I am partial to the simplest of visualizations in a business data context, I love a simple Bar Chart just as much as a Chord or Fisher-Yates Shuffle. 6: Turbocharging Data Visuals with Storytelling.

Visualization 124

Visualization Strategy Interactive Statistics 124

Alation

AUGUST 26, 2021

HBR Review May/June 2017. BI leverages and synthesizes data from analytics, data mining, and visualization tools to deliver quick snapshots of business health to key stakeholders, and empower those people to make better choices. Source: “What’s Your Data Strategy?” by Leandro DalleMule and Thomas H. Data Intelligence and Metadata.

Metadata 64

Metadata Data Governance Dashboards Software 64

Domino Data Lab

SEPTEMBER 9, 2019

Next let’s use the displaCy library to visualize the parse tree for that sentence: In [4]: from spacy import displacy?? The displaCy library provides an excellent way to visualize named entities: In [15]: displacy.render(doc, style="ent"). lemma – a root form of the word. part of speech. for a, b in pairs:?.

Deep Learning 110

Deep Learning Machine Learning Visualization Data Science 110