About Matthew Mayo

Matthew Mayo is Machine Learning Researcher and the Editor of KDnuggets, the seminal online Data Science and Machine Learning resource. He is particularly interested in unsupervised learning, deep neural networks, natural language processing, algorithm design and optimization, and distributed approaches to data processing and analysis. Matthew holds a Master's degree in CS and a graduate diploma in Data Mining. Email him at mattmayo at kdnuggets[dot]com.

Matthew Mayo Posts (282)

• Which Data Science / Machine Learning methods and algorithms did you use in 2018/2019 for a real-world application? - 09 Apr 2019
  
  Which Data Science / Machine Learning methods and algorithms did you use in 2018/2019 for a real-world application? Take part in the latest KDnuggets survey and have your say.
• Another 10 Free Must-See Courses for Machine Learning and Data Science - 05 Apr 2019
  
  Check out another follow-up collection of free machine learning and data science courses to give you some spring study ideas.
• What Does GPT-2 Think About the AI Arms Race? - 01 Apr 2019
  
  It may be April first, but that doesn't mean you will necessarily be fooled by GPT-2's views on the AI arms race. Why not have a read for fun and to see what the language generation model is capable of.
• Where Analytics, Data Science, Machine Learning Were Applied: Trends and Analysis - 07 Mar 2019
  
  CRM/Consumer analytics, health care, banking, finance, and science were the top sectors in 2018. The greatest increases were in mobile apps, investment, security, entertainment, and social policy, while fraud detection, retail, advertising, direct marketing, and social media saw the greatest declines.
• Another 10 Free Must-Read Books for Machine Learning and Data Science - 06 Mar 2019
  
  Here's a third set of 10 free books for machine learning and data science. Have a look to see if something catches your eye, and don't forget to check the previous installments for reading material while you're here.
• Where did you apply Analytics, Data Science, Machine Learning in 2018? - 25 Feb 2019
  
  Where did you apply Analytics, Machine Learning, and Data Science in 2018? Take part in the latest KDnuggets poll to share your input, and see what others have to say.
• Intuitive Visualization of Outlier Detection Methods - 05 Feb 2019
  
  Check out this visualization for outlier detection methods, and the Python project from which it comes, a toolkit for easily implementing outlier detection methods on your own.
• Trending Deep Learning Github Repositories - 01 Feb 2019
  
  Check these pair of resources for trending and top GitHub deep learning repositories for some new ideas on what to be looking out for.
• 7 Steps to Mastering Basic Machine Learning with Python — 2019 Edition - 29 Jan 2019
  
  With a new year upon us, I thought it would be a good time to revisit the concept and put together a new learning path for mastering machine learning with Python. With these 7 steps you can master basic machine learning with Python!
• NLP Overview: Modern Deep Learning Techniques Applied to Natural Language Processing - 08 Jan 2019
  
  Trying to keep up with advancements at the overlap of neural networks and natural language processing can be troublesome. That's where the today's spotlighted resource comes in.