Wayback Machine
364 captures
23 Sep 2022 - 15 May 2026
Dec JAN Feb
16
2025 2026 2027
success
fail
About this capture
COLLECTED BY
Organization: Archive Team
Formed in 2009, the Archive Team (not to be confused with the archive.org Archive-It Team) is a rogue archivist collective dedicated to saving copies of rapidly dying or deleted websites for the sake of history and digital heritage. The group is 100% composed of volunteers and interested parties, and has expanded into a large amount of related projects for saving online and digital history.

History is littered with hundreds of conflicts over the future of a community, group, location or business that were "resolved" when one of the parties stepped ahead and destroyed what was there. With the original point of contention destroyed, the debates would fall to the wayside. Archive Team believes that by duplicated condemned data, the conversation and debate can continue, as well as the richness and insight gained by keeping the materials. Our projects have ranged in size from a single volunteer downloading the data to a small-but-critical site, to over 100 volunteers stepping forward to acquire terabytes of user-created data to save for future generations.

The main site for Archive Team is at archiveteam.org and contains up to the date information on various projects, manifestos, plans and walkthroughs.

This collection contains the output of many Archive Team projects, both ongoing and completed. Thanks to the generous providing of disk space by the Internet Archive, multi-terabyte datasets can be made available, as well as in use by the Wayback Machine, providing a path back to lost websites and work.

Our collection has grown to the point of having sub-collections for the type of data we acquire. If you are seeking to browse the contents of these collections, the Wayback Machine is the best first stop. Otherwise, you are free to dig into the stacks to see what you may find.

The Archive Team Panic Downloads are full pulldowns of currently extant websites, meant to serve as emergency backups for needed sites that are in danger of closing, or which will be missed dearly if suddenly lost due to hard drive crashes or server failures.

Collection: ArchiveBot: The Archive Team Crowdsourced Crawler
ArchiveBot is an IRC bot designed to automate the archival of smaller websites (e.g. up to a few hundred thousand URLs). You give it a URL to start at, and it grabs all content under that URL, records it in a WARC, and then uploads that WARC to ArchiveTeam servers for eventual injection into the Internet Archive (or other archive sites).

To use ArchiveBot, drop by #archivebot on EFNet. To interact with ArchiveBot, you issue commands by typing it into the channel. Note you will need channel operator permissions in order to issue archiving jobs. The dashboard shows the sites being downloaded currently.

There is a dashboard running for the archivebot process at http://www.archivebot.com.

ArchiveBot's source code can be found at https://github.com/ArchiveTeam/ArchiveBot.

TIMESTAMPS
loading
The Wayback Machine - https://web.archive.org/web/20260116220321/https://learn.microsoft.com/en-us/dotnet/machine-learning/
Skip to main content

This browser is no longer supported.

Upgrade to Microsoft Edge to take advantage of the latest features, security updates, and technical support.

Download Microsoft Edge More info about Internet Explorer and Microsoft Edge
Read in English Edit

Share via

Facebook x.com LinkedIn Email

ML.NET documentation

Learn how to use open-source ML.NET to build custom machine learning models and integrate them into apps. Tutorials, code examples, and more show you how.

ML.NET basics

Overview

  • Overview of ML.NET
  • What is the ML.NET API?
  • What is Model Builder?

video

  • Machine learning basics

Concept

  • Machine learning tasks & algorithms
  • How to choose an algorithm

Get started

  • ML.NET on Q&A

Get started in 10 minutes

Quickstart

  • Get started with the ML.NET API (code-first)
  • Set up Model Builder in Visual Studio (low-code)
  • Install the CLI on macOS, Windows, or Linux (low-code)

Tutorials

Training

  • Predictive maintenance (Model Builder)

Tutorial

  • Analyze website comment sentiment (Model Builder)
  • Predict prices (Model Builder)
  • Categorize health violations (Model Builder & SQL Server)
  • Categorize support issues (API)
  • Classify images with Image Classification API (API)
  • Use object detection to recognize traffic signs (Model Builder)
  • Detect objects in images (API)
  • Detect anomalies in product sales (API)
  • Forecast bike rental demand (API & SQL Server)
  • Build a movie recommender (API)

How-to guides

How-To Guide

  • Load data from various sources
  • Prepare data for building a model
  • Train & evaluate a model
  • Make predictions with a trained model
  • Save & load a trained model
  • Retrain a model

Reference

Reference

  • ML.NET API reference
  • ML.NET CLI reference
  • ML.NET samples
en-us
Your Privacy Choices
  • AI Disclaimer
  • Previous Versions
  • Blog
  • Contribute
  • Privacy
  • Terms of Use
  • Trademarks
  • © Microsoft 2026
✕

Wait! Don't Go Yet 🚀

Get our FREE eBook "10 Programming Tips That Changed Everything" when you subscribe!

No spam. Unsubscribe anytime.