You're missing out on some cool features if you're building applications in .NET Core 3 and not exploiting the new features in C# 8. Here's what Peter thinks are the ones you'll find most useful.
When training data won't fit into machine memory, a streaming data loader using an internal memory buffer can help. Dr. James McCaffrey of Microsoft Research shows how.
- By James McCaffrey
- 04/01/2021
Dr. James McCaffrey of Microsoft Research explains how to evaluate, save and use a trained regression model, used to predict a single numeric value such as the annual revenue of a new restaurant based on variables such as menu prices, number of tables, location and so on.
- By James McCaffrey
- 03/12/2021
The goal of a regression problem is to predict a single numeric value, for example, predicting the annual revenue of a new restaurant based on variables such as menu prices, number of tables, location and so on.
- By James McCaffrey
- 03/03/2021
Dr. James McCaffrey of Microsoft Research presents the second of four machine learning articles that detail a complete end-to-end production-quality example of neural regression using PyTorch.
- By James McCaffrey
- 02/11/2021
Dr. James McCaffrey of Microsoft Research presents the first in a series of four machine learning articles that detail a complete end-to-end production-quality example of neural regression using PyTorch.
- By James McCaffrey
- 02/02/2021
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 model accuracy.
- By James McCaffrey
- 01/25/2021
Blazor's Virtualize component will let you display long lists faster without writing a lot of code. If you want to take full advantage of the component, however, you'll need a relatively smart repository to back it up.
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.
- By James McCaffrey
- 01/04/2021
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.
- By James McCaffrey
- 12/15/2020
Dr. James McCaffrey of Microsoft Research kicks off a four-part series on multi-class classification, designed to predict a value that can be one of three or more possible discrete values.
- By James McCaffrey
- 12/04/2020
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
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
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
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
Thanks to Chris Sainty and Remi Bourgarel, working with local storage from a Blazor application running either in the browser or out of it is relatively easy. Testing your code can be equally easy but only if you set up support the real world of network connections.
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
Mobilize.Net, an "automated modernization" specialist headed by a former Microsoft corporate VP, has upgraded its Visual Basic upgrade tool to target .NET Core, the open source, cross-platform successor of the Windows-only .NET Framework.
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