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).
This resource is part of a series on specific topics related to data science: regression, clustering, neural networks, deep learning, Hadoop, decision trees, ensembles, correlation,… Read More »19 Great Articles About Natural Language Processing (NLP)
Here we describe a simple methodology to produce predictive scores that are consistent over time and compatible across various clients, to allow for meaningful comparisons… Read More »How to Stabilize Data Systems, to Avoid Decay in Model Performance
It all depends on the classes that you attended. Some are worth listing, some are best not to mention. Here I review of few of… Read More »Should you Add your Coursera, Udacity, or DataCamp Training to your Resume?
Many of the following statistical tests are rarely discussed in textbooks or in college classes, much less in data camps. Yet they help answer a… Read More »A Plethora of Original, Not Well-Known Statistical Tests
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
