SQL Server and SDS


Entity Framework Core 6: What Developers Want

Microsoft outlined its plan for Entity Framework Core 6, which in November will take its place as the data access component of the landmark .NET 6, a long-term support (LTS) release that will mark Microsoft's transition from the Windows-only .NET Framework to an open source, cross-platform umbrella offering of all things .NET.

Azure SQL Database Ranked Among Top 3 Databases of 2020

Microsoft touted the inclusion of Azure SQL Database among the top three databases of 2020 in a popularity ranking by DB-Engines, which collects and manages information about database management systems, updating its lists monthly.

Multi-Class Classification Using PyTorch: Training

Dr. James McCaffrey of Microsoft Research continues his four-part series on multi-class classification, designed to predict a value that can be one of three or more possible discrete values, by explaining neural network training.

Multi-Class Classification Using PyTorch: Defining a Network

Dr. James McCaffrey of Microsoft Research explains how to define a network in installment No. 2 of his four-part series that will present a complete end-to-end production-quality example of multi-class classification using a PyTorch neural network.

Binary Classification Using PyTorch: Model Accuracy

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.

4 Experts List Favorite New EF Core 5.0 Features

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.

Binary Classification Using PyTorch: Training

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.

.NET for Apache Spark Debuts in Version 1.0

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 8 Preview Supports .NET 5, but with Breaking Changes

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.

Binary Classification Using PyTorch: Defining a Network

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.

Binary Classification Using PyTorch: Preparing Data

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.

Entity Framework Core 5 RC1 Is Feature Complete, Ready for Production

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.

How to Create and Use a PyTorch DataLoader

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.

Data Prep for Machine Learning: Splitting

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.

Data Prep for Machine Learning: Encoding

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.

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