Explore >> Select a destination
|
You are here 
|
andrewjaffe.net | ||
| | | | |
dustintran.com
|
|
| | | | | One aspect I always enjoy about machine learning is that questions often go back to the basics. The field essentially goes into an existential crisis every dozen years-rethinking our tools and asking foundational questions such as "why neural networks" or "why generative models".1 This was a theme in my conversations during NIPS 2016 last week, where a frequent topic was on the advantages of a Bayesian perspective to machine learning. Not surprisingly, this appeared as a big discussion point during the p... | |
| | | | |
deepai.org
|
|
| | | | | Bayesian inference refers to the application of Bayes' Theorem in determining the updated probability of a hypothesis given new information. | |
| | | | |
gameswithwords.fieldofscience.com
|
|
| | | | | In this week's New Yorker , Jonah Lehrer shows once again just how hard it is to do good science journalism if you are not yourself a scient... | |
| | | | |
statsandr.com
|
|
| | | This article explains in details what is the normal or Gaussian distribution, its importance in statistics and how to test if your data is normally distributed | ||
