Dr. James McCaffrey of Microsoft Research explains the k-means++ technique for data clustering, the process of grouping data items so that similar items are in the same cluster, for human examination to see if any interesting patterns have emerged or for software systems such as anomaly detection.
- By James McCaffrey
- 05/06/2020
Microsoft recently beefed up the .NET and Java SDKs for Azure Cosmos DB, a globally distributed, multi-model database service that helps users and developers elastically and independently scale throughput and storage across Azure regions with a click of a button.
VSM Senior Technical Editor Dr. James McCaffrey, of Microsoft Research, explains why inverting a matrix -- one of the more common tasks in data science and machine learning -- is difficult and presents code that you can use as-is, or as a starting point for custom matrix inversion scenarios.
- By James McCaffrey
- 04/07/2020
Microsoft engineer Sam Xu says "it’s time to move OData to .NET 5" and in a new blog post he shows how to do just that.
In announcing today's second preview of the big, unifying .NET 5 that's going GA in November, Microsoft revealed the next-gen platform is already handling 50 percent of the traffic to the company's main .NET website.
A radial basis function network (RBF network) is a software system that's similar to a single hidden layer neural network, explains Dr. James McCaffrey of Microsoft Research, who uses a full C# code sample and screenshots to show how to train an RBF network classifier.
- By James McCaffrey
- 03/24/2020
Dr. James McCaffrey of Microsoft Research explains how to design a radial basis function (RBF) network -- a software system similar to a single hidden layer neural network -- and describes how an RBF network computes its output.
- By James McCaffrey
- 03/13/2020
Resident data scientist Dr. James McCaffrey of Microsoft Research turns his attention to evolutionary optimization, using a full code download, screenshots and graphics to explain this machine learning technique used to train many types of models by modeling the biological processes of natural selection, evolution, and mutation.
- By James McCaffrey
- 02/21/2020
Eric Vogel uses code samples and screenshots to demonstrate how to do Entity Framework Core migrations in a .NET Core application through the command line and in code.
Dr. James McCaffrey of Microsoft Research uses a full code program, examples and graphics to explain multi-class logistic regression, an extension technique that allows you to predict a class that can be one of three or more possible values, such as predicting the political leaning of a person (conservative, moderate, liberal) based on age, sex, annual income and so on.
- By James McCaffrey
- 02/11/2020
After earlier explaining how to compute disorder and split data in his exploration of machine learning decision tree classifiers, resident data scientist Dr. James McCaffrey of Microsoft Research now shows how to use the splitting and disorder code to create a working decision tree classifier.
- By James McCaffrey
- 01/22/2020
There are plenty of reasons to move traditional ASP.NET web apps -- part of the old .NET Framework -- to the new cross-platform direction, ASP.NET Core, but beware it will require some "heavy lifting," Microsoft says.
Using a decision tree classifier from a machine learning library is often awkward because it usually must be customized and library decision trees have many complex supporting functions, says resident data scientist Dr. James McCaffrey, so when he needs a decision tree classifier, he always creates one from scratch. Here's how.
- By James McCaffrey
- 01/21/2020
Microsoft-centric technologies are featured prominently in a new examination of the top in-demand programming skills published by careers site Dice.com.
Dr. James McCaffrey of Microsoft Research uses code samples and screen shots to explain perceptron classification, a machine learning technique that can be used for predicting if a person is male or female based on numeric predictors such as age, height, weight, and so on. It's mostly useful to provide a baseline result for comparison with more powerful ML techniques such as logistic regression and k-nearest neighbors.
- By James McCaffrey
- 01/07/2020