Author and Publisher at MLtechniques.com. Machine learning scientist, mathematician, book author (Wiley), patent owner, former post-doc at Cambridge University, former VC-funded executive, with 20+ years of corporate experience including CNET, NBC, Visa, Wells Fargo, Microsoft, eBay. Vincent also founded and co-founded a few start-ups, including one with a successful exit (Data Science Central acquired by Tech Target).
The original article is no longer available. Similar (and more comprehensive) material is available below. Example of underfitted, well-fitted and overfitted models Content Regression What… Read More »Linear regression in Python: Using numpy, scipy, and statsmodels
I have used synthetic data sets many times for simulation purposes, most recently in my articles Six degrees of Separations between any two Datasets and How to Lie… Read More »Surprising Uses of Synthetic Random Data Sets
I have used synthetic data sets many times for simulation purposes, most recently in my articles Six degrees of Separations between any two Datasets and… Read More »Surprising Uses of Synthetic Random Data Sets
Probably the worst error is thinking there is a correlation when that correlation is purely artificial. Take a data set with 100,000 variables, say with… Read More »Common Errors in Machine Learning due to Poor Statistics Knowledge
Many statistics, such as correlations or R-squared, depend on the sample size, making it difficult to compare values computed on two data sets of different… Read More »Simple Trick to Normalize Correlations, R-squared, and so on
These 25 queries using our own data science search engine, return hundreds of articles and resources, sorted by popularity and recency. This resource is part… Read More »25 Search Queries Featuring Hundreds of Categorized Articles and Resources
Originally posted by John Bowden. There is a meeting of the world’s most renowned scientists once in two years. These meetings are held to tackle… Read More »Making New Drugs with a Dose of Artificial Intelligence
First days after the celebration of the New Year is the time when looking back we can analyze our actions, promises and draw conclusions whether… Read More »Top 10 Technology Trends of 2019
Originally posted here. From detecting anomalies to understanding what are the key elements in a network, or highlighting communities, graph analytics reveal information that… Read More »Finding insights with graph analytics
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, decision trees, ensembles, correlation, Python,… Read More »23 Statistical Concepts Explained in Simple English – Part 7
