pymc-learn is a library for practical probabilistic machine learning in Python. The difference between the two models is that pymc-learn estimates model parameters using Bayesian inference algorithms ...

This repository contains the main codebase for the undergraduate thesis: "Fusión de sensores para el seguimiento de trayectorias en vehículos autónomos mediante modelos probabilísticos" (Sensor Fusion ...

One day in November, a product strategist we’ll call Michelle (not her real name), logged into her LinkedIn account and switched her gender to male. She also changed her name to Michael, she told ...

Learn the Adagrad optimization algorithm, how it works, and how to implement it from scratch in Python for machine learning models. #Adagrad #Optimization #Python Trump administration looking to sell ...

In structural health monitoring (SHM), uncertainties from environmental noise and modeling errors affect damage detection accuracy. This paper introduces a new concept: the Fast Fourier Transform ...

How do the algorithms that populate our social media feeds actually work? In a piece for Time Magazine excerpted from his recent book Robin Hood Math, Noah Giansiracusa sheds light on the algorithms ...

If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle the easiest pieces first. But this kind of sorting has a cost.

ABSTRACT: The Tabu Search heuristic can be used to optimise the WET (waste to energy technology). Developments were made to the basic Tabu Search to adapt it to the optimisation problem. This paper ...