IBM Big Data Hub

JULY 6, 2023

.” “Data science” was first used as an independent discipline in 2001. The fields have evolved such that to work as a data analyst who views, manages and accesses data, you need to know Structured Query Language (SQL) as well as math, statistics, data visualization (to present the results to stakeholders) and data mining.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

Domino Data Lab

APRIL 3, 2019

This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form. Welcome back to our monthly burst of themes and conferences.

Data Governance 84

Data Governance Machine Learning Metadata Data Science 84

Domino Data Lab

JULY 22, 2019

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. Greg Linden ‘s article about splitting the website on Amazon. We have an article on this on Domino.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

JANUARY 6, 2019

What are the projected risks for companies that fall behind for internal training in data science? In terms of teaching and learning data science, Project Jupyter is probably the biggest news over the past decade – even though Jupyter’s origins go back to 2001! Data visualization for prediction accuracy ( credit: R2D3 ).

Data Science 56

Data Science Machine Learning Visualization Reporting 56

Domino Data Lab

MAY 20, 2021

In this article we discuss why fitting models on imbalanced datasets is problematic, and how class imbalance is typically addressed. Figure 3 shows visual explanation of how SMOTE generates synthetic observations in this case. Chawla et al. Indeed, in the original paper Chawla et al. References. Banko, M., & Brill, E.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

Domino Data Lab

AUGUST 8, 2019

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. If you’ve never participated in a Foo event, check out this article by Scott Berkun. The probabilistic nature changes the risks and process required.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Domino Data Lab

JULY 9, 2019

In 2001, Bill Cleveland writes this article saying, “You are doing it wrong.” This was one of several such articles, but that’s another talk. Then we can drill down and say what are the individual articles that over-index for that group or for that topic. That is an example of a descriptive tool.

Data Science 112

Data Science Machine Learning Advertising Modeling 112