After 28+ years of publishing and editing KDnuggets, I am retiring and transitioning KDnuggets to Matthew Mayo, who will become the new editor-in-chief. I want to share with you my story of KDnuggets and highlight some of the useful nuggets of experience I learned along this amazing journey.
The hiring run for data scientists continues along at a strong clip around the world. But, there are other emerging roles that are demonstrating key value to organizations that you should consider based on your existing or desired skill sets.
Find out the major differences between a Data Analyst and a Data Scientist, and read the author's pointers on what they would recommend you to do if you wish to make that transition from Data Analyst to Data Scientist.
Natural language processing research and applications are moving forward rapidly. Several trends have emerged on this progress, and point to a future of more exciting possibilities and interesting opportunities in the field.
The notion of self-service BI tools caught an expectation that they could provide a magic formula for easily helping everyone understand all the data. But, such an end-result isn't occurring in practice. To identify a better approach, we need to take a step back and determine what problem is actually trying to be solved.
After a pause, we will be resuming KDnuggets Top Blog Rewards Program, starting with blogs published on KDnuggets in December. The program will be bigger, with $3,000 (USD) divided among top 8 most viewed guest blogs. Original blogs rewarded at the rate of 3X of reposts. Submit your original blog to KDnuggets first !
Beginners in the field can often have many misconceptions about machine learning that sometimes can be a make-it-or-break-it moment for the individual switching careers or starting fresh. This article clearly describes the ground truth realities about learning new ML skills and eventually working professionally as a machine learning engineer.
There remain critical challenges in machine learning that, if left resolved, could lead to unintended consequences and unsafe use of AI in the future. As an important and active area of research, roadmaps are being developed to help guide continued ML research and use toward meaningful and robust applications.