Explore >> Select a destination
|
You are here 
|
www.unofficialgoogledatascience.com | ||
| | | | |
fa.bianp.net
|
|
| | | | | The Langevin algorithm is a simple and powerful method to sample from a probability distribution. It's a key ingredient of some machine learning methods such as diffusion models and differentially private learning. In this post, I'll derive a simple convergence analysis of this method in the special case when the ... | |
| | | | |
blog.fastforwardlabs.com
|
|
| | | | | By Chris and Melanie. The machine learning life cycle is more than data + model = API. We know there is a wealth of subtlety and finesse involved in data cleaning and feature engineering. In the same vein, there is more to model-building than feeding data in and reading off a prediction. ML model building requires thoughtfulness both in terms of which metric to optimize for a given problem, and how best to optimize your model for that metric! | |
| | | | |
matbesancon.xyz
|
|
| | | | | Learning by doing: predicting the outcome. | |
| | | | |
aurimas.eu
|
|
| | | a.k.a. why you should (not ?) use uninformative priors in Bayesian A/B testing. | ||
