Computer science

Introduction to Linear Regression

A data scientist's first goal is to find underlying relations within the variables of a dataset. Several statistical and machine learning methods can be used to discover such relations. Once uncovered, this information can be applied to everyday problems. For example, in clinical medicine, a predictive model based on clinical data can help clinicians guide a patient's treatment by offering insights that might not have otherwise been taken into account. Simple linear regression One of the most basic methods available to [...]

Implementing a “Siamese” Neural Network with Mariana 1.0

Mariana was previously introduced in this blog by Geneviève in her May post Machine learning in life science. The Mariana codebase is currently standing on github at the third release candidate before the launch of the stable 1.0 release. This new version incorporates a large refactorization effort as well as many new features (a complete list of the changes found in the 1.0 version can be found in the changelog). I am taking this opportunity to present here a small tutorial on extending the [...]

By | November 7, 2016|Categories: Computer science, Data Analysis, Machine learning, Python|0 Comments

Fast network transfers?

Recently, everyone and their mother started using various tools in order to optimize large data transfer to, from and between supercomputers. Historically, we have seen tools like FDT, BBCP that tried to exceed the performance obtained from other transfer methods, like scp, rsync, ftp, etc. One tool in particular is now gaining traction and is being deployed on most supercomputers: GridFTP and its front-end Globus. The Globus frontend interface. Before jumping into the bandwagon, I thought it would [...]

By | October 13, 2016|Categories: Computer science, Performance, Test|0 Comments