Matthew Mayo

KDnuggets Managing Editor

Matthew Mayo (@mattmayo13) holds a master's degree in computer science and a graduate diploma in data mining. As managing editor of KDnuggets & Statology, and contributing editor at Machine Learning Mastery, Matthew aims to make complex data science concepts accessible. His professional interests include natural language processing, language models, machine learning algorithms, and exploring emerging AI. He is driven by a mission to democratize knowledge in the data science community. Matthew has been coding since he was 6 years old.

Comparing Clustering Techniques: A Concise Technical Overview

By Matthew Mayo, KDnuggets Managing Editor on September 26, 2016 in Algorithms, Clustering, K-means, Machine Learning
A wide array of clustering techniques are in use today. Given the widespread use of clustering in everyday data mining, this post provides a concise technical overview of 2 such exemplar techniques.
Data Science Basics: 3 Insights for Beginners

By Matthew Mayo, KDnuggets Managing Editor on September 22, 2016 in Algorithms, Beginners, Datasets, Overfitting, Supervised Learning, Unsupervised Learning
For data science beginners, 3 elementary issues are given overview treatment: supervised vs. unsupervised learning, decision tree pruning, and training vs. testing datasets.
Support Vector Machines: A Concise Technical Overview

By Matthew Mayo, KDnuggets Managing Editor on September 21, 2016 in Algorithms, Machine Learning, Support Vector Machines
Support Vector Machines remain a popular and time-tested classification algorithm. This post provides a high-level concise technical overview of their functionality.
The Great Algorithm Tutorial Roundup

By Matthew Mayo, KDnuggets Managing Editor on September 20, 2016 in Algorithms, Clustering, Decision Trees, K-nearest neighbors, Machine Learning, PCA, Poll, random forests algorithm, Regression, Statistics, Text Mining, Time Series, Visualization
This is a collection of tutorials relating to the results of the recent KDnuggets algorithms poll. If you are interested in learning or brushing up on the most used algorithms, as per our readers, look here for suggestions on doing so!
The (Not So) New Data Scientist Venn Diagram

By Matthew Mayo, KDnuggets Managing Editor on September 12, 2016 in Data Science, Data Scientist, Drew Conway, Venn Diagram, Yanir Seroussi
This post outlines a (relatively) new(er) Data Science-related Venn diagram, giving an update to Conway's classic, and providing further fuel for flame wars and heated disagreement.
Introducing Dask for Parallel Programming: An Interview with Project Lead Developer

By Matthew Mayo, KDnuggets Managing Editor on September 7, 2016 in Analytics, Continuum Analytics, Dask, Data Science, Distributed Computing, Parallelism, Python, Scientific Computing
Introducing Dask, a flexible parallel computing library for analytics. Learn more about this project built with interactive data science in mind in an interview with its lead developer.
Top Machine Learning Projects for Julia

By Matthew Mayo, KDnuggets Managing Editor on August 19, 2016 in Deep Learning, Julia, Machine Learning, Open Source, scikit-learn
Julia is gaining traction as a legitimate alternative programming language for analytics tasks. Learn more about these 5 machine learning related projects.
Big Data Key Terms, Explained

By Matthew Mayo, KDnuggets Managing Editor on August 11, 2016 in 3Vs of Big Data, Apache Spark, Big Data, Business Intelligence, Cloud Computing, Data Warehouse, Explained, Hadoop, Key Terms, Predictive Analytics
Just getting started with Big Data, or looking to iron out the wrinkles in your current understanding? Check out these 20 Big Data-related terms and their concise definitions.
Understanding the Bias-Variance Tradeoff: An Overview

By Matthew Mayo, KDnuggets Managing Editor on August 8, 2016 in Bias, Cross-validation, Model Performance, Variance
A model's ability to minimize bias and minimize variance are often thought of as 2 opposing ends of a spectrum. Being able to understand these two types of errors are critical to diagnosing model results.
Yann LeCun Quora Session Overview

By Matthew Mayo, KDnuggets Managing Editor on August 1, 2016 in Deep Learning, Generative Adversarial Network, Quora, Yann LeCun
Here is a quick oversight, with excerpts, of the Yann LeCun Quora Session which took place on Thursday July 28, 2016.

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