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 (276)

• 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.
• Approaches to Text Summarization: An Overview - 03 Jan 2019
  
  This article will present the main approaches to text summarization currently employed, as well as discuss some of their characteristics.
• 3 More Google Colab Environment Management Tips - 02 Jan 2019
  
  This is a short collection of lessons learned using Colab as my main coding learning environment for the past few months. Some tricks are Colab specific, others as general Jupyter tips, and still more are filesystem related, but all have proven useful for me.
• Papers with Code: A Fantastic GitHub Resource for Machine Learning - 31 Dec 2018
  
  Looking for papers with code? If so, this GitHub repository, a clearinghouse for research papers and their corresponding implementation code, is definitely worth checking out.
• The Essence of Machine Learning - 28 Dec 2018
  
  And so now, as an exercise in what may seem to be semantics, let's explore some 30,000 feet definitions of what machine learning is.
• 10 More Must-See Free Courses for Machine Learning and Data Science - 20 Dec 2018
  
  Have a look at this follow-up collection of free machine learning and data science courses to give you some winter study ideas.
• Industry Predictions: AI, Machine Learning, Analytics & Data Science Main Developments in 2018 and Key Trends for 2019 - 18 Dec 2018
  
  This is a collection of data science, machine learning, analytics, and AI predictions for next year from a number of top industry organizations. See what the insiders feel is on the horizon for 2019!