Category: Data Science

Author: mtdearing Without a well-defined approach for collecting and structuring training data, launching an AI initiative becomes an uphill battle. These six recommendations will help […] Read More

Author: Vincent Granville Probably the worst error is thinking there is a correlation when that correlation is purely artificial. Take a data set with 100,000 […] Read More

Author: Vincent Granville Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for […] Read More

Author: ajit jaokar Can an ethical and algorithmically transparent cloud kitchen prevent future Amazon fires?   We often view AI with suspicion – but AI […] Read More

Author: Gregory Piatetsky As a media partner for O’Reilly, KDnuggets is pleased to offer to our readers a chance to win a 2-day Bronze Conference […] Read More

Author: Jorge Castanon Photo by chuttersnap on Unsplash Machine learning is a hot topic in research and industry, with new methodologies developed all the time. The speed and […] Read More

Author: mtdearing With the pervasive importance of NLP in so many of today’s applications of deep learning, find out how advanced translation techniques can be […] Read More

Author: Bill Schmarzo Imagine an advanced fighter aircraft is patrolling a hostile conflict area and a bogie suddenly appears on radar accelerating aggressively at them. The […] Read More

Author: Gregory PS Editor Algorithms Notes for Professionals – Free Book; 10 simple Linux tips which save 50% of my time in the command line; […] Read More

Author: William Vorhies Summary:  True prescriptive analytics requires the use of real optimization techniques that very few applications actually use.  Here’s a refresher on optimization […] Read More