Category: Data Science

Author: Stephanie Glen Fifty years, ago, the lines between “data analysis” and “statistical analysis” were pretty clear. But as data analysis evolved, those lines became […] Read More

Author: Matthew Dearing We’ve seen many predictions for what new advances are expected in the field of AI and machine learning. Here, we review a […] Read More

Author: Igor Bobriakov Machine learning (ML) is a hot topic nowadays. Everyone speaks about the new programming paradigm, models are implemented in very different domains, […] Read More

Author: Matt Mayo Editor Also: Global #AI Index ranks 54 countries: US is currently ahead. China is second, but growing faster; RStudio Projects and Working […] Read More

Author: mtdearing With the explosion of the field of AI/ML impacting so many applications and industries, there is great value coming out of recent progress. […] Read More

Author: William Vorhies Summary:  Workforce forecasting and scheduling applications are rapidly upgrading their use of AI.  Techniques of time series forecasting ranging from the simple […] Read More

Author: Gregory Piatetsky The results of latest KDnuggets Poll on AutoML are quite interesting. While most respondents were not happy with AutoML performance, the opinions […] Read More

Author: /u/datascience-bot Bleep Bloop. Welcome to this week’s entering & transitioning thread! This thread is for any questions about getting started, studying, or transitioning into […] 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: mtdearing Academic credentials and experience with previous machine learning projects are important for kicking off a data science career. However, landing your first job […] Read More