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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.
04/07/2020
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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.
03/24/2020
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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.
03/13/2020
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Microsoft's latest update of ML.NET Model Builder adds a recommendation scenario to the machine learning (ML) framework, along with image classification model training functionality.
03/04/2020
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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.
02/21/2020
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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.
02/11/2020
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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.
01/22/2020
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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.
01/21/2020
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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.
01/07/2020
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Microsoft announced an update to the Model Builder component of its ML.NET machine learning framework, boosting image classification and adding "try your model" functionality for predictions with sample input.
11/13/2019
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Dr. James McCaffrey of Microsoft Research uses a full code sample and screenshots to demonstrate how to create a naive Bayes classification system when the predictor values are numeric, using the C# language without any special code libraries.
11/12/2019
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Here's a hands-on tutorial from bona-fide data scientist Dr. James McCaffrey of Microsoft Research to get you up to speed with machine learning development using C#, complete with code listings and graphics.
11/07/2019
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While the question of artificial intelligence someday replacing computer programmers is still being debated, Microsoft is steadily using AI advances to boost their productivity, this week announcing whole line completions and refactoring.
11/05/2019
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Microsoft Research's Dr. James McCaffrey show how to perform binary classification with logistic regression using the Microsoft ML.NET code library. The goal of binary classification is to predict a value that can be one of just two discrete possibilities, for example, predicting if a person is male or female
10/18/2019
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Dr. James McCaffrey provides hands-on examples in introducing ML.NET, for machine learning prediction models, and AutoML, which automatically examines different ML algorithms, finds the best one, and creates a Visual Studio project with the C# code backing the best model, along with C# code that shows how to use the trained model to make a prediction.
09/30/2019
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Microsoft Research data scientist Dr. James McCaffrey explains what neural network Glorot initialization is and why it's the default technique for weight initialization.
09/05/2019
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We caught up with Henk Boelman, Microsoft AI MVP and Cloud AI Architect, to learn more about what's exciting in AI, his favorite features in Microsoft Cognitive Services and Windows IoT and the latest updates on his upcoming day-long hands-on lab for Live! 360, "Build Your Own A.I. Powered Robot."
08/16/2019
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By John K. Waters
Microsoft Research is unveiling its latest AI initiative, one that aims to help "democratize AI" with a new open-source framework that will leverage blockchain technology.
07/31/2019
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Data scientist Dr. James McCaffrey begins a series on presenting and explaining the most common modern techniques used for neural networks, for which over the past couple of years there have been many small but significant changes in the default techniques used.
07/29/2019
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Updated Python functionality heads a list of enhancements to Microsoft's Bot Framework SDK, facilitating conversational artificial intelligence development for a number of application channels, such as Skype, Teams, Slack and so on.
07/23/2019
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Microsoft's investment will turbocharge OpenAI's efforts toward artificial general intelligence (AGI) and drive development of next-generation solutions and platforms.
07/23/2019
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Microsoft's open source machine learning framework, ML.NET, has been updated to version 1.2, continuing to add features to help .NET developers use their familiar tools and languages to infuse ML functionality into their applications.
07/17/2019
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TensorWatch, a new AI debugging and visualization tool from Microsoft Research, is now available as an open source offering on GitHub, where it's "under heavy development with a goal of providing a platform for debugging machine learning in one easy to use, extensible, and hackable package."
06/27/2019
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After hitting version 1.0 last month, Microsoft's open source, cross-platform machine learning framework ML.NET has received its first update, which adds functionality and addresses developer concerns about usability and stability.
06/12/2019
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Dr. James McCaffrey of Microsoft Research uses Python code samples and screenshots to explain naive Bayes classification, a machine learning technique used to predict the class of an item based on two or more categorical predictor variables, such as predicting the gender (0 = male, 1 = female) of a person based on occupation, eye color and nationality.
05/14/2019