IBM Big Data Hub

JULY 6, 2023

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Ultimately, data science is used in defining new business problems that machine learning techniques and statistical analysis can then help solve. appeared first on IBM Blog.

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

Alation

MARCH 29, 2022

As Business Objects founder Bernard Liautaud notes in e-Business Intelligence: Turning Information Into Knowledge Into Profit (McGraw-Hill, 2001), the lack of ad hoc data access causes IT staff to drown in requests. Subscribe to Alation's Blog. Slow requirements led technology leaders to demand proactive business intelligence.

Business Intelligence 96

Business Intelligence Reporting Data mining Data-driven 96

The Unofficial Google Data Science Blog

JUNE 30, 2016

Identification We now discuss formally the statistical problem of causal inference. We start by describing the problem using standard statistical notation. The field of statistical machine learning provides a solution to this problem, allowing exploration of larger spaces. 2001): 5-32. we drop the $i$ index.

Statistics 44

Statistics Optimization Modeling Experimentation 44

The Unofficial Google Data Science Blog

AUGUST 27, 2019

But importance sampling in statistics is a variance reduction technique to improve the inference of the rate of rare events, and it seems natural to apply it to our prevalence estimation problem. 2] Lawrence Brown, Tony Cai, Anirban DasGupta (2001). Statistical Science. Statistics in Biopharmaceutical Research, 2010. [4]

Metrics 98

Metrics Statistics Uncertainty Optimization 98

Domino Data Lab

JULY 22, 2019

This blog post provides a concise session summary, a video, and a written transcript. He was saying this doesn’t belong just in statistics. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. I can point to the year 2001. Session Summary.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

JANUARY 6, 2019

And my favorite topic: what are some of the best books, blogs, podcasts, etc., 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! for beginning study in data science? Learning Data Science.

Data Science 56

Data Science Machine Learning Reporting Visualization 56