Category: Machine Learning

Author: Jason Brownlee Statistical hypothesis tests report on the likelihood of the observed results given an assumption, such as no association between variables or no […] Read More

Author: Jason Brownlee Correlation is a measure of the association between two variables. It is easy to calculate and interpret when both variables have a […] Read More

Author: Scott Morley | Laboratory for Nuclear Science The Argonne Leadership Computing Facility (ALCF), a U.S. Department of Energy (DOE) Office of Science User Facility, […] Read More

Author: Rob Matheson | MIT News Office Designing new molecules for pharmaceuticals is primarily a manual, time-consuming process that’s prone to error. But MIT researchers […] Read More

Author: Jason Brownlee There is an ocean of books on statistics; where do you start? A big problem in choosing a beginner book on statistics […] Read More

Author: Jason Brownlee The use of randomness is an important part of the configuration and evaluation of machine learning algorithms. From the random initialization of […] Read More

Author: Zygmunt Z. Go to Source

Author: Paul Rivenberg “In some ways you can compare what we are trying to do to self-driving cars.” MIT postdoc Cristina Rea is describing her […] Read More

Author: Jason Brownlee Tom Mitchell’s classic 1997 book “Machine Learning” provides a chapter dedicated to statistical methods for evaluating machine learning models. Statistics provides an […] Read More

Author: Jason Brownlee The machine learning practitioner has a tradition of algorithms and a pragmatic focus on results and model skill above other concerns such […] Read More