About Matthew Dearing

Matthew T. Dearing is an applications developer and an Associate Editor of KDnuggets. With a BA in Physics and MS in Computer Science, Matthew keeps a pulse on the latest advancements as a top-rated editor of scientific and technical publications from clients around the world. With interests ranging from machine learning to neurotechnologies, Matthew also supports STEM informal educational opportunities for all ages.

Matthew Dearing Posts (6)

  • Silver BlogTop 10 AI, Machine Learning Research Articles to know - 30 Jan 2020
    We’ve seen many predictions for what new advances are expected in the field of AI and machine learning. Here, we review a “data set” based on what researchers were apparently studying at the turn of the decade to take a fresh glimpse into what might come to pass in 2020.
  • Gold Blog10 Free Must-read Books on AI - 05 Nov 2019
    Artificial Intelligence continues to fill the media headlines while scientists and engineers rapidly expand its capabilities and applications. With such explosive growth in the field, there is a great deal to learn. Dive into these 10 free books that are must-reads to support your AI study and work.
  • Silver Blog12 Deep Learning Researchers and Leaders - 23 Sep 2019
    Our list of deep learning researchers and industry leaders are the people you should follow to stay current with this wildly expanding field in AI. From early practitioners and established academics to entrepreneurs and today’s top corporate influencers, this diverse group of individuals is leading the way into tomorrow’s deep learning landscape.
  • Gold BlogTop 10 Best Podcasts on AI, Analytics, Data Science, Machine Learning - 29 Jul 2019
    Check out our latest Top 10 Most Popular Data Science and Machine Learning podcasts available on iTunes. Stay up to date in the field with these recent episodes and join in with the current data conversations.
  • Why Machine Learning is vulnerable to adversarial attacks and how to fix it - 13 Jun 2019
    Machine learning can process data imperceptible to humans to produce expected results. These inconceivable patterns are inherent in the data but may make models vulnerable to adversarial attacks. How can developers harness these features to not lose control of AI?
  • AI in the Family: how to teach machine learning to your kids - 28 May 2019
    AI is all the rage with today’s programmers, but what about the next generation? Machine learning can be introduced to young ones just now learning about code, and you can help spark their interest.