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3 | 3 | This is an ever-evolving page where samples and content from the ML.NET community are highlighted, so anyone in the community can also take advantage of these additional samples. |
4 | 4 |
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5 | 5 | However, note that Microsoft does not maintain the samples in the list below. |
6 | | - |
| 6 | + |
7 | 7 | | Name | Description | ML Tasks or area of focus | API status | Owner | |
8 | 8 | |-------------------------------------|---------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------|--------------------------------------------------------------------------|-----------------------------| |
| 9 | +| [Malicious Packet Detection](https://github.com/mikekberg/ml-hackathon-2020) | Use anomaly detection with ML.NET to detect malicious network activity. | anomaly detection model | ML.NET v1.5.2 | Kudos for Mike Berg (mikekberg) | |
| 10 | +| [Silencer](https://github.com/WalternativE/Silencer) | A Chrome browser extension written in F# that scans your Twitter DMs and uses ML.NET to filter out toxic text. | classification model | ML.NET v1.5.2 | Kudos for Gregor Beyerle (WalternativE) | |
| 11 | +| [Smart Labeling](https://github.com/dcostea/SmartLabeling) | A tool that uses ML.NET to create labeled datasets. | image classification model | ML.NET v1.5.2 | Kudos for Daniel Costea (dcostea) | |
| 12 | +| [PhotoBombers](https://github.com/photobombers/photobomb) | An automated object tagging utility for photos using ML.NET | image classification model | ML.NET v1.5.2 | Kudos for Paul Amazona (whatevergeek) | |
| 13 | +| [Stonks Inc!](https://github.com/Schentrup-Software/AutomaticStockTrader) | Use ML.NET to predict future stock prices. | forecasting model | ML.NET v1.5.2 | Kudos for Joey Schentrup (joeySchentrup) | |
| 14 | +| [Wine Lovers](https://github.com/M1rceaDogaru/virtual-som) | Use ML.NET to suggest a type of wine based on a free-form description. | classification model | ML.NET v1.5.0 | Kudos for Mircea Dogaru (M1rceaDogaru) | |
| 15 | +| [Predicting System Load](https://github.com/Sumeetgaara/Predicting-load-of-a-system-using-ML) | Use ML.NET to predict load of withdrawal service of a bank for a given day. | forecasting model | ML.NET v1.5.2 | Kudos for Sumeet More (sumbagaara) and Rohan Ghodke | |
| 16 | +| [Real-Time Object Detection](https://github.com/Schentrup-Software/AutomaticStockTrader) | Use ML.NET apply object detection to real-time web cam footage | object detection model | ML.NET v1.5.2 | Kudos for Sam (msadengineer) | |
| 17 | +| [Visual Inspection & Classification of X-Ray Chest Disease](https://github.com/olowoyinka/ML_ImageClassification_ChestDisease) | Use ML.NET to visually inspect a sample of X-Ray chest images and predict the sample image according to the categories of Chest Disease | image classification model | ML.NET v1.4 | Kudos for Yinka Olowofela (olowoyinka) | |
9 | 18 | | [COVID-19 Exploratory Data Analysis using .NET](https://github.com/praveenraghuvanshi/covid-19) | Use .NET DataFrame API and ML.NET to perform analysis on COVID-19 dataset and visualize the trends of virus spread in various countries | forecasting model | ML.NET v1.5 | Kudos for Praveen Raghuvanshi (praveenraghuvanshi) | |
10 | 19 | | [Rom-com or not rom-com](https://github.com/davidgristwood/rom-com-or-not-rom-com/) | ML.NET project designed to run a machine learning model over a text document and determine if it exhibits the classic characteristics of a rom-com film script. | multi-class classification model | ML.NET v1.4 | Kudos for David Gristwood (davidgristwood) | |
11 | 20 | | [Photo-Search](https://github.com/Tak-Au/Photo-Search) | Sample WPF app running an ONNX model which was previously built with Keras and exported to ONNX model format. | Deep Learning, Image classification | ML.NET v0.9 and .NET Core 3.0 | Kudos for Tak-Au | |
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