A “quick” introduction to PyMC3 and Bayesian models, Part I
In this post, I give a “brief”, practical introduction using a specific and hopefully relate-able example drawn from real data.…
Added by Robert R. Tucci on December 17, 2019 at 12:00pm — No Comments
In practice, the Data Scientist wants to know which formula they will write in their Excel sheet when they enter all the data available into it: Bayes’ or usual?
The answer is that it depends: if all the data is well…
ContinueAdded by Marcia Ricci Pinheiro on February 18, 2019 at 4:50am — No Comments
The sigmatoid Bayesian, according to SEP, connects to a reverend called Thomas Bayes (circa 1700).
Bayesian Probability is like a reaction to the Mathematical Probability: what about our…
ContinueAdded by Marcia Ricci Pinheiro on February 16, 2019 at 11:30pm — No Comments
An Introduction to Bayesian Reasoning
You might be using Bayesian techniques in your data science without knowing it! And if you're not, then it could enhance the power of your analysis. This blog post, part 1 of 2, will demonstrate how Bayesians employ probability distributions to add information when fitting models, and reason about uncertainty of the model's fit.
Grab a coin. How fair is the coin? What is the probability…
ContinueAdded by Sean Owen on February 13, 2019 at 8:00am — 3 Comments
In this post, I give a “brief”, practical introduction using a specific and hopefully relate-able example drawn from real data.…
Added by Jesus Ramos on May 8, 2018 at 10:00am — No Comments
Since their early days, humans have had an important, often antagonistic relationship with uncertainty; we try to kill it everywhere we find it. Without an explanation for many natural phenomena, humans invented gods to explain them, and without certainty of the future, they consulted oracles.
It was…
ContinueAdded by Jesus Ramos on May 8, 2018 at 9:00am — No Comments
The use of formal statistical methods to analyse quantitative data in data science has increased considerably over the last few years. One such approach, Bayesian Decision Theory (BDT), also known as Bayesian Hypothesis Testing and Bayesian inference, is a fundamental statistical approach that quantifies the tradeoffs between various decisions using…
Added by Kostas Hatalis on March 15, 2018 at 12:00pm — No Comments
Bayesian Nonparametrics is a class of models with a potentially infinite number of parameters. High flexibility and expressive power of this approach enables better data modelling compared to parametric methods.
Bayesian Nonparametrics is used in problems where a dimension of interest grows with data, for example, in problems where the number of features is not fixed but allowed to vary as we observe more…
ContinueAdded by Luba Belokon on October 12, 2017 at 3:00pm — No Comments
High Performance Computing (HPC) plus data science allows public and private organizations get…
ContinueAdded by Michael Walker on September 17, 2013 at 12:28pm — 1 Comment
Business analytics comes in three (3) general flavors: descriptive, predictive and prescriptive. See: …
ContinueAdded by Michael Walker on August 27, 2013 at 2:00pm — No Comments
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
1999
Posted 1 March 2021
© 2021 TechTarget, Inc.
Powered by
Badges | Report an Issue | Privacy Policy | Terms of Service
Most Popular Content on DSC
To not miss this type of content in the future, subscribe to our newsletter.
Other popular resources
Archives: 2008-2014 | 2015-2016 | 2017-2019 | Book 1 | Book 2 | More
Most popular articles