Found 24 talks width keyword Data mining

Planetary systems have been found systematically orbiting main sequence stars and red giants. But the detection of planets per se during the white dwarf phase has been more elusive with only 3 systems.  We have, however, ample indirect evidence  of the existence of planetary debris around these systems in the form of material acreted onto the white dwarf, disks and even planetesimals. In this talk, I will review how we can put the pieces together: how we can reconcile what we see in white dwarfs with what we can infer regarding the evolution of planetary systems from the main sequence phase.

We will introduce several ways in which trivially embarrassingly parallel tasks can be run in laptops and desktops. We will introduce command-line tools such as GNU parallel and Kiko. We will then focus on simple techniques for optimisation of scientific computations in python. We will cover parallel computing with multiprocessing, acceleration of functions via numba, and GPU computing with cupy. The goal is to provide an easy roadmap for python code optimisation methods that can applied on already existing code, without writing a single line of C or FORTRAN.

In this talk, we shall review the impact of the neutrino properties on the different cosmological observables. We shall also present the latest cosmological constraints on the neutrino masses and on the effective number of relativistic species. Special attention would be devoted to the role of neutrinos in solving the present cosmological tensions.

Pandas is an open source Python package that is widely used for data analysis. It is a powerful ally for data munging/wrangling and databases manipulation/visualisation, and a must-have tool for Data Scientists. In this seminar we will have a general overview on its functionality and we will run over some of the reasons of its large success in the Data Science community.

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: Supervised learning: classification and regression
Lecture 4

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: Supervised learning: classification and regression
Lecture 3

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: Deep learning
Lecture 4

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: Data challenges and solutions in forthcoming surveys
Lecture 4

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: General overview on the use of machine learning techniques in astronomy
Lecture 4

Series: XXX Canary Islands Winter School of Astrophysics: Big Data in Astronomy
Topic: Machine learning methods for non-supervised classification and dimension reduction techniques
Lecture 4