From e3e369b98fcdf88d5c603ea36734dd2fd79b67c2 Mon Sep 17 00:00:00 2001 From: Morten Hjorth-Jensen Date: Sat, 27 Jul 2019 23:09:19 +0200 Subject: [PATCH] Update README.md --- README.md | 1 - 1 file changed, 1 deletion(-) diff --git a/README.md b/README.md index 63e1a188a..037d31725 100644 --- a/README.md +++ b/README.md @@ -19,7 +19,6 @@ This course aims thus at discussing many of the central algorithms used in Data - Learn about basic data analysis, statistical analysis, Bayesian statistics, Monte Carlo sampling, data optimization and machine learning; - Be capable of extending the acquired knowledge to other systems and cases; - Have an understanding of central algorithms used in data analysis and machine learning; -- Gain knowledge of central aspects of Monte Carlo methods, Markov chains, Gibbs samplers and their possible applications; - Understand linear methods for regression and classification, from ordinary least squares, via Lasso and Ridge to Logistic regression; - Learn about various neural networks and deep learning methods for supervised and unsupervised learning; - Learn about about decision trees and random forests