In the final article of a four-part series on binary classification using PyTorch, Dr. James McCaffrey of Microsoft Research shows how to evaluate the accuracy of a trained model, save a model to file, and use a model to make predictions.
- By James McCaffrey
- 11/24/2020
Experts in the open source community surrounding Microsoft's recent EF Core 5.0 release have weighed in with their favorite new features in the object-database mapper for .NET.
Dr. James McCaffrey of Microsoft Research continues his examination of creating a PyTorch neural network binary classifier through six steps, here addressing step No. 4: training the network.
- By James McCaffrey
- 11/04/2020
The open source project .NET for Apache Spark has debuted in version 1.0, finally vaulting the C# and F# programming languages into Big Data first-class citizenship.
ASP.NET Core OData, which debuted in July 2018, is out in a v8.0 preview that for the first time supports the upcoming .NET 5 milestone release.
Dr. James McCaffrey of Microsoft Research tackles how to define a network in the second of a series of four articles that present a complete end-to-end production-quality example of binary classification using a PyTorch neural network, including a full Python code sample and data files.
- By James McCaffrey
- 10/14/2020
Dr. James McCaffrey of Microsoft Research kicks off a series of four articles that present a complete end-to-end production-quality example of binary classification using a PyTorch neural network, including a full Python code sample and data files.
- By James McCaffrey
- 10/05/2020
The first release candidate for Entity Framework 5 -- Microsoft's object-database mapper for .NET -- has shipped with a go live license, ready for production.
Dr. James McCaffrey of Microsoft Research provides a full code sample and screenshots to explain how to create and use PyTorch Dataset and DataLoader objects, used to serve up training or test data in order to train a PyTorch neural network.
- By James McCaffrey
- 09/10/2020
Dr. James McCaffrey of Microsoft Research explains how to programmatically split a file of data into a training file and a test file, for use in a machine learning neural network for scenarios like predicting voting behavior from a file containing data about people such as sex, age, income and so on.
- By James McCaffrey
- 09/01/2020
Dr. James McCaffrey of Microsoft Research uses a full code program and screenshots to explain how to programmatically encode categorical data for use with a machine learning prediction model such as a neural network classification or regression system.
- By James McCaffrey
- 08/12/2020
Dr. James McCaffrey of Microsoft Research uses a full code sample and screenshots to show how to programmatically normalize numeric data for use in a machine learning system such as a deep neural network classifier or clustering algorithm.
- By James McCaffrey
- 08/04/2020
Microsoft shipped the seventh preview of Entity Framework Core 5.0, boosting its data access technology with a factory to create DbContext instances and more.
After previously detailing how to examine data files and how to identify and deal with missing data, Dr. James McCaffrey of Microsoft Research now uses a full code sample and step-by-step directions to deal with outlier data
- By James McCaffrey
- 07/14/2020
Turning his attention to the extremely time-consuming task of machine learning data preparation, Dr. James McCaffrey of Microsoft Research explains how to examine data files and how to identify and deal with missing data.
- By James McCaffrey
- 07/06/2020