Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Cayley-Hamilton technique. Compared to other matrix inverse algorithms, Cayley-Hamilton is very simple and as a nice side effect gives you the matrix determinant. However, Cayley-Hamilton is not suitable for use with large matrices.
- By James McCaffrey
- 06/16/2025
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric value. A linear SVR model uses an unusual error/loss function and cannot be trained using standard techniques, and so particle swarm optimization training is used.
- By James McCaffrey
- 06/03/2025
Bring AI to your database! Learn how to build smarter apps with vector search in SQL Server & Azure Cosmos DB -- no extra AI stack required.
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton iteration is simple and easy to customize, but the technique is relatively slow.
- By James McCaffrey
- 05/15/2025
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of linear regression with two-way interactions between predictor variables. Compared to standard linear regression, which predicts a single numeric value based only on a linear combination of predictor values, linear regression with interactions can handle more complex data while retaining a high level of model interpretability.
- By James McCaffrey
- 05/02/2025
SQL development is evolving fast, and Microsoft's Drew Skwiers-Koballa will explain it all in a featured session at the VS Live! @ Microsoft HQ developer conference being held at the company's Redmond campus in August.
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of Nadaraya-Watson kernel regression using the C# language. NW kernel regression is simple to implement and is especially effective for small datasets.
- By James McCaffrey
- 04/18/2025
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric value. A linear SVR model uses an unusual error/loss function and cannot be trained using standard simple techniques, and so evolutionary optimization training is used.
- By James McCaffrey
- 04/01/2025
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric value with an assurance such as, "The predicted y value is 0.6789 and there's roughly a 90% chance the prediction will be greater than or equal to the true y value."
- By James McCaffrey
- 03/17/2025
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demo of Poisson regression, where the goal is to predict a count of things arriving, such as the number of telephone calls received in a 10-minute interval at a call center. When your source data is close to mathematically Poisson distributed, Poisson regression is simple and effective.
- By James McCaffrey
- 03/03/2025
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the naive Bayes regression technique, where the goal is to predict a single numeric value. Compared to other machine learning regression techniques, naive Bayes regression is usually less accurate, but is simple, easy to implement and customize, works on both large and small datasets, is highly interpretable, and doesn't require tuning any hyperparameters.
- By James McCaffrey
- 02/20/2025
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the random neighborhoods regression technique, where the goal is to predict a single numeric value. Compared to other ML regression techniques, advantages are that it can handle both large and small datasets, and the results are highly interpretable.
- By James McCaffrey
- 02/03/2025
Microsoft experts are making the rounds educating developers about the company's new, opinionated, cloud-ready stack for building observable, production ready, distributed, cloud-native applications with .NET.
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the gradient boosting regression technique, where the goal is to predict a single numeric value. Compared to existing library implementations of gradient boosting regression, a from-scratch implementation allows much easier customization and integration with other .NET systems.
- By James McCaffrey
- 01/15/2025
Serving tens of millions of developers, Microsoft's dev team for Python in Visual Studio Code shipped a new release with three major new features, including a "full" language server mode for Pylance, which provides language-specific "smarts," including IntelliSense.