How machines process and understand human language Everything we express (either verbally or in written) carries huge amounts of information. The topic we choose, our to...
Not all these contributions were from 2018, but the few selected below were among the most visited in 2018. Some were heavily featured, so it does not mean that they repr...
This article was written by Kevin Hartnett. The nearest neighbor problem asks where a new point fits into an existing data set. A few researchers set out to prove that th...
In a previous post, I have provided a discussion of model stacking, a popular approach in data science competitions for boosting predictive performance. Since then, the ...
Summary: Despite hundreds of projects and thousands of data scientists devoted to bringing AI/ML to healthcare, adoption remains low and slow. A good portion of this ...
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, ...
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, c...
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, c...
Machine learning algorithms are extremely computationally intensive and time consuming when they must be trained on large amounts of data. Typical processors are not opti...
Pooled, also referred to as “converged”, clusters in a unified data environment support disparate workload better than separate, siloed clusters. Vendors now provide ...