From 1e2456a986785c56c3751d463c549dc058401fd5 Mon Sep 17 00:00:00 2001 From: Dan Moseley Date: Sun, 6 May 2018 22:12:07 -0700 Subject: [PATCH 01/13] Update README.md Enlarge readme including prerequisites. --- README.md | 67 ++++++++++++++++++++++++++++++++++++------------------- 1 file changed, 44 insertions(+), 23 deletions(-) diff --git a/README.md b/README.md index 5414d424f2..bc9370e47b 100644 --- a/README.md +++ b/README.md @@ -1,30 +1,17 @@ -# Machine Learning in .NET +# Machine Learning for .NET -ML.NET provides state-of-the-art machine learning (ML) algorithms, transforms, and components, and powers ML pipelines in many Microsoft products. Developed and used internally at Microsoft for over 5 years, the goal is to make ML.NET useful for all developers, data scientists, and information workers and helpful in all products, services, and devices. +[ML.NET](https://www.microsoft.com/net/learn/apps/machine-learning-and-ai/ml-dotnet) provides state-of-the-art machine learning (ML) algorithms, transforms, and components, and powers ML pipelines in many Microsoft products. Developed and used internally at Microsoft for over 5 years, the goal is to make ML.NET useful for all developers, data scientists, and information workers and helpful in all products, services, and devices. -### Build Status +ML.NET runs on Windows, Linux, and macOS - any platform where 64 bit [.NET Core](https://github.com/dotnet/core) or later is available. -Coming soon +With ML.NET you can use the latest ML algorithms to create and evaluate a model from training data. Once you have a model, you can add to your app just a few lines of .NET code to make predictions from the model. -### Installation - -You can install ML.NET NuGet from the CLI using: -``` -dotnet add package Microsoft.ML -``` - -From package manager: -``` -Install-Package Microsoft.ML -``` -For an example of getting started with .NET Core, see [here](https://www.microsoft.com/net/learn/get-started). +### Examples -### Building -To build ML.NET from source go to [developers guide](https://github.com/dotnet/machinelearning/blob/master/Documentation/project-docs/developer-guide.md) +Imagine you want to predict the sale price of a house. Given a large dataset of information about other houses, including their sale prices, you can use ML.NET to create and evaluate a model. Then, you can deploy the model with your app. -### Example +Here's a different example, with code, to train a model to predict sentiment from text samples. (You can see the complete sample [here](https://github.com/dotnet/machinelearning/blob/master/test/Microsoft.ML.Tests/Scenarios/Scenario3_SentimentPrediction.cs)): -Simple snippet to train a model for sentiment classification (See the complete sample [here](https://github.com/dotnet/machinelearning/blob/master/test/Microsoft.ML.Tests/Scenarios/Scenario3_SentimentPrediction.cs)): ```C# var pipeline = new LearningPipeline(); pipeline.Add(new TextLoader(dataPath, separator: ",")); @@ -33,7 +20,7 @@ pipeline.Add(new FastTreeBinaryClassifier()); var model = pipeline.Train(); ``` -Infer the trained model for predictions: +Now from the model we can make inferences (predictions): ```C# SentimentData data = new SentimentData @@ -46,7 +33,37 @@ SentimentPrediction prediction = model.Predict(data); Console.WriteLine("prediction: " + prediction.Sentiment); ``` -### Code of Conduct +### Installation + +First ensure you have installed [.NET Core 2.0](https://www.microsoft.com/net/learn/get-started) or later. ML.NET also works on the .NET Framework. Note that ML.NET currently must run in a 64 bit process. + +Once you have an app, you can install ML.NET NuGet from the .NET Core CLI using: +``` +dotnet add package Microsoft.ML +``` + +or from the package manager: +``` +Install-Package Microsoft.ML +``` + +Or alternatively you can add the Microsoft.ML package from within Visual Studio's NuGet package manager. + +### Releases + +The current release is 0.1. Check out the [release notes](https://github.com/dotnet/machinelearning/blob/master/Documentation/release-notes/0.1/release-0.1.md). + +### Building + +To build ML.NET from source please visit our [developers guide.](https://github.com/dotnet/machinelearning/blob/master/Documentation/project-docs/developer-guide.md) + +### Contributing + +We welcome contributions! Please review our [contribution guide](https://github.com/dotnet/machinelearning/blob/master/CONTRIBUTING.md). + +### Community + +Please join our community on Gitter [![Join the chat at https://gitter.im/dotnet/corefx](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/dotnet/?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) This project has adopted the code of conduct defined by the [Contributor Covenant](http://contributor-covenant.org/) to clarify expected behavior in our community. For more information, see the [.NET Foundation Code of Conduct](https://dotnetfoundation.org/code-of-conduct). @@ -61,4 +78,8 @@ ML.NET is a [.NET Foundation](http://www.dotnetfoundation.org/projects) project. There are many .NET related projects on GitHub. -- [.NET home repo](https://github.com/Microsoft/dotnet) - links to 100s of .NET projects, from Microsoft and the community. \ No newline at end of file +- [.NET home repo](https://github.com/Microsoft/dotnet) - links to 100s of .NET projects, from Microsoft and the community. + +### Build Status + +Coming soon From 0d9a4182e98d18812c71fd8bf6226e5fe9959b7e Mon Sep 17 00:00:00 2001 From: Dan Moseley Date: Sun, 6 May 2018 22:15:22 -0700 Subject: [PATCH 02/13] Update README.md --- README.md | 13 +++++-------- 1 file changed, 5 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index bc9370e47b..1f42b88d1a 100644 --- a/README.md +++ b/README.md @@ -35,6 +35,8 @@ Console.WriteLine("prediction: " + prediction.Sentiment); ### Installation +The current release is 0.1. Check out the [release notes](https://github.com/dotnet/machinelearning/blob/master/Documentation/release-notes/0.1/release-0.1.md). + First ensure you have installed [.NET Core 2.0](https://www.microsoft.com/net/learn/get-started) or later. ML.NET also works on the .NET Framework. Note that ML.NET currently must run in a 64 bit process. Once you have an app, you can install ML.NET NuGet from the .NET Core CLI using: @@ -49,19 +51,17 @@ Install-Package Microsoft.ML Or alternatively you can add the Microsoft.ML package from within Visual Studio's NuGet package manager. -### Releases - -The current release is 0.1. Check out the [release notes](https://github.com/dotnet/machinelearning/blob/master/Documentation/release-notes/0.1/release-0.1.md). - ### Building To build ML.NET from source please visit our [developers guide.](https://github.com/dotnet/machinelearning/blob/master/Documentation/project-docs/developer-guide.md) +Live build status is coming soon. + ### Contributing We welcome contributions! Please review our [contribution guide](https://github.com/dotnet/machinelearning/blob/master/CONTRIBUTING.md). -### Community +## Community Please join our community on Gitter [![Join the chat at https://gitter.im/dotnet/corefx](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/dotnet/?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) @@ -80,6 +80,3 @@ There are many .NET related projects on GitHub. - [.NET home repo](https://github.com/Microsoft/dotnet) - links to 100s of .NET projects, from Microsoft and the community. -### Build Status - -Coming soon From 47972c1f0088124d2ca25a3ea6b3cfc723252809 Mon Sep 17 00:00:00 2001 From: Dan Moseley Date: Sun, 6 May 2018 22:17:59 -0700 Subject: [PATCH 03/13] Update README.md Move examples down --- README.md | 54 +++++++++++++++++++++++++++--------------------------- 1 file changed, 27 insertions(+), 27 deletions(-) diff --git a/README.md b/README.md index 1f42b88d1a..3b60ccab48 100644 --- a/README.md +++ b/README.md @@ -6,33 +6,6 @@ ML.NET runs on Windows, Linux, and macOS - any platform where 64 bit [.NET Core] With ML.NET you can use the latest ML algorithms to create and evaluate a model from training data. Once you have a model, you can add to your app just a few lines of .NET code to make predictions from the model. -### Examples - -Imagine you want to predict the sale price of a house. Given a large dataset of information about other houses, including their sale prices, you can use ML.NET to create and evaluate a model. Then, you can deploy the model with your app. - -Here's a different example, with code, to train a model to predict sentiment from text samples. (You can see the complete sample [here](https://github.com/dotnet/machinelearning/blob/master/test/Microsoft.ML.Tests/Scenarios/Scenario3_SentimentPrediction.cs)): - -```C# -var pipeline = new LearningPipeline(); -pipeline.Add(new TextLoader(dataPath, separator: ",")); -pipeline.Add(new TextFeaturizer("Features", "SentimentText")); -pipeline.Add(new FastTreeBinaryClassifier()); -var model = pipeline.Train(); -``` - -Now from the model we can make inferences (predictions): - -```C# -SentimentData data = new SentimentData -{ - SentimentText = "Today is a great day!" -}; - -SentimentPrediction prediction = model.Predict(data); - -Console.WriteLine("prediction: " + prediction.Sentiment); -``` - ### Installation The current release is 0.1. Check out the [release notes](https://github.com/dotnet/machinelearning/blob/master/Documentation/release-notes/0.1/release-0.1.md). @@ -68,6 +41,33 @@ Please join our community on Gitter [![Join the chat at https://gitter.im/dotnet This project has adopted the code of conduct defined by the [Contributor Covenant](http://contributor-covenant.org/) to clarify expected behavior in our community. For more information, see the [.NET Foundation Code of Conduct](https://dotnetfoundation.org/code-of-conduct). +### Examples + +Imagine you want to predict the sale price of a house. Given a large dataset of information about other houses, including their sale prices, you can use ML.NET to create and evaluate a model. Then, you can deploy the model with your app. + +Here's a different example, with code, to train a model to predict sentiment from text samples. (You can see the complete sample [here](https://github.com/dotnet/machinelearning/blob/master/test/Microsoft.ML.Tests/Scenarios/Scenario3_SentimentPrediction.cs)): + +```C# +var pipeline = new LearningPipeline(); +pipeline.Add(new TextLoader(dataPath, separator: ",")); +pipeline.Add(new TextFeaturizer("Features", "SentimentText")); +pipeline.Add(new FastTreeBinaryClassifier()); +var model = pipeline.Train(); +``` + +Now from the model we can make inferences (predictions): + +```C# +SentimentData data = new SentimentData +{ + SentimentText = "Today is a great day!" +}; + +SentimentPrediction prediction = model.Predict(data); + +Console.WriteLine("prediction: " + prediction.Sentiment); +``` + ## License ML.NET is licensed under the [MIT license](LICENSE). From 82b06105b363558da59303a83835e8a6c060ef8a Mon Sep 17 00:00:00 2001 From: Dan Moseley Date: Sun, 6 May 2018 22:18:47 -0700 Subject: [PATCH 04/13] Update README.md 2nd level headings --- README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 3b60ccab48..fd47a11e1a 100644 --- a/README.md +++ b/README.md @@ -6,7 +6,7 @@ ML.NET runs on Windows, Linux, and macOS - any platform where 64 bit [.NET Core] With ML.NET you can use the latest ML algorithms to create and evaluate a model from training data. Once you have a model, you can add to your app just a few lines of .NET code to make predictions from the model. -### Installation +## Installation The current release is 0.1. Check out the [release notes](https://github.com/dotnet/machinelearning/blob/master/Documentation/release-notes/0.1/release-0.1.md). @@ -24,13 +24,13 @@ Install-Package Microsoft.ML Or alternatively you can add the Microsoft.ML package from within Visual Studio's NuGet package manager. -### Building +## Building To build ML.NET from source please visit our [developers guide.](https://github.com/dotnet/machinelearning/blob/master/Documentation/project-docs/developer-guide.md) Live build status is coming soon. -### Contributing +## Contributing We welcome contributions! Please review our [contribution guide](https://github.com/dotnet/machinelearning/blob/master/CONTRIBUTING.md). @@ -41,7 +41,7 @@ Please join our community on Gitter [![Join the chat at https://gitter.im/dotnet This project has adopted the code of conduct defined by the [Contributor Covenant](http://contributor-covenant.org/) to clarify expected behavior in our community. For more information, see the [.NET Foundation Code of Conduct](https://dotnetfoundation.org/code-of-conduct). -### Examples +## Examples Imagine you want to predict the sale price of a house. Given a large dataset of information about other houses, including their sale prices, you can use ML.NET to create and evaluate a model. Then, you can deploy the model with your app. From 5328592e52010c26328c669fc85f188f57cc88a8 Mon Sep 17 00:00:00 2001 From: danmosemsft Date: Sun, 6 May 2018 22:32:57 -0700 Subject: [PATCH 05/13] Add logo --- Documentation/logo-ml-net.svg | 1 + 1 file changed, 1 insertion(+) create mode 100644 Documentation/logo-ml-net.svg diff --git a/Documentation/logo-ml-net.svg b/Documentation/logo-ml-net.svg new file mode 100644 index 0000000000..a0688a7eea --- /dev/null +++ b/Documentation/logo-ml-net.svg @@ -0,0 +1 @@ + \ No newline at end of file From 8ee9bddbe33dc81fae9fb6d4b35ad5ffc0dd2383 Mon Sep 17 00:00:00 2001 From: danmosemsft Date: Sun, 6 May 2018 22:38:12 -0700 Subject: [PATCH 06/13] Shrink logo --- Documentation/logo-ml-net.svg | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Documentation/logo-ml-net.svg b/Documentation/logo-ml-net.svg index a0688a7eea..72d7bc00e8 100644 --- a/Documentation/logo-ml-net.svg +++ b/Documentation/logo-ml-net.svg @@ -1 +1 @@ - \ No newline at end of file + \ No newline at end of file From e9460eba949ae49d5d44d88ade3abc414a08afd9 Mon Sep 17 00:00:00 2001 From: Dan Moseley Date: Sun, 6 May 2018 22:43:08 -0700 Subject: [PATCH 07/13] Update README.md --- README.md | 16 +++++++++++++--- 1 file changed, 13 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index fd47a11e1a..ed3762a03f 100644 --- a/README.md +++ b/README.md @@ -1,13 +1,23 @@ + + # Machine Learning for .NET -[ML.NET](https://www.microsoft.com/net/learn/apps/machine-learning-and-ai/ml-dotnet) provides state-of-the-art machine learning (ML) algorithms, transforms, and components, and powers ML pipelines in many Microsoft products. Developed and used internally at Microsoft for over 5 years, the goal is to make ML.NET useful for all developers, data scientists, and information workers and helpful in all products, services, and devices. +[ML.NET](https://www.microsoft.com/net/learn/apps/machine-learning-and-ai/ml-dotnet) is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers. -ML.NET runs on Windows, Linux, and macOS - any platform where 64 bit [.NET Core](https://github.com/dotnet/core) or later is available. +ML.NET allows .NET developers to develop their own models and infuse custom ML into their applications without prior expertise in developing or tuning machine learning models. + +ML.NET was originally developed in Microsoft Research and evolved into a significant framework over the last decade and is used across many product groups in Microsoft like Windows, Bing, Power Point, Excel and more. -With ML.NET you can use the latest ML algorithms to create and evaluate a model from training data. Once you have a model, you can add to your app just a few lines of .NET code to make predictions from the model. +With this first preview release ML.NET enables ML tasks like classification (e.g. support text classification, sentiment analysis) and regression (e.g. forecasting, price-prediction). + +Along with these ML capabilities this first release of ML.NET also brings the first draft of .NET APIs for training models, using models for predictions, as well as the core components of this framework such as learning algorithms, transforms, and core ML data structures. + +ML.NET is first and foremost a framework which means it can be extended to add popular ML Libraries like TensorFlow, Accord.NET and CNTK. The design of the framework will prioritize usability, extensibility, and toolability, without sacrificing performance. ## Installation +ML.NET runs on Windows, Linux, and macOS - any platform where 64 bit [.NET Core](https://github.com/dotnet/core) or later is available. + The current release is 0.1. Check out the [release notes](https://github.com/dotnet/machinelearning/blob/master/Documentation/release-notes/0.1/release-0.1.md). First ensure you have installed [.NET Core 2.0](https://www.microsoft.com/net/learn/get-started) or later. ML.NET also works on the .NET Framework. Note that ML.NET currently must run in a 64 bit process. From aca4e45807905425839a0e85828e0132bca04578 Mon Sep 17 00:00:00 2001 From: danmosemsft Date: Sun, 6 May 2018 23:27:05 -0700 Subject: [PATCH 08/13] Remove logo --- Documentation/logo-ml-net.svg | 1 - 1 file changed, 1 deletion(-) delete mode 100644 Documentation/logo-ml-net.svg diff --git a/Documentation/logo-ml-net.svg b/Documentation/logo-ml-net.svg deleted file mode 100644 index 72d7bc00e8..0000000000 --- a/Documentation/logo-ml-net.svg +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file From 0c4b35b745646af64d8a147d7f12faa80054d795 Mon Sep 17 00:00:00 2001 From: Dan Moseley Date: Sun, 6 May 2018 23:35:36 -0700 Subject: [PATCH 09/13] Update README.md --- README.md | 16 +++++++--------- 1 file changed, 7 insertions(+), 9 deletions(-) diff --git a/README.md b/README.md index ed3762a03f..51e1cc90f5 100644 --- a/README.md +++ b/README.md @@ -6,13 +6,13 @@ ML.NET allows .NET developers to develop their own models and infuse custom ML into their applications without prior expertise in developing or tuning machine learning models. -ML.NET was originally developed in Microsoft Research and evolved into a significant framework over the last decade and is used across many product groups in Microsoft like Windows, Bing, Power Point, Excel and more. +ML.NET was originally developed in Microsoft Research and evolved into a significant framework over the last decade and is used across many product groups in Microsoft like Windows, Bing, PowerPoint, Excel and more. -With this first preview release ML.NET enables ML tasks like classification (e.g. support text classification, sentiment analysis) and regression (e.g. forecasting, price-prediction). +With this first preview release ML.NET enables ML tasks like classification (e.g. support text classification, sentiment analysis) and regression (e.g. price-prediction). -Along with these ML capabilities this first release of ML.NET also brings the first draft of .NET APIs for training models, using models for predictions, as well as the core components of this framework such as learning algorithms, transforms, and core ML data structures. +Along with these ML capabilities this first release of ML.NET also brings the first draft of .NET APIs for training models, using models for predictions, as well as the core components of this framework such as learning algorithms, transforms, and ML data structures. -ML.NET is first and foremost a framework which means it can be extended to add popular ML Libraries like TensorFlow, Accord.NET and CNTK. The design of the framework will prioritize usability, extensibility, and toolability, without sacrificing performance. +ML.NET is first and foremost a framework which means it will be extensible to integrate popular ML libraries like TensorFlow, Accord.NET and CNTK. The design of the framework will prioritize usability, extensibility, and toolability, without sacrificing performance. ## Installation @@ -36,13 +36,13 @@ Or alternatively you can add the Microsoft.ML package from within Visual Studio' ## Building -To build ML.NET from source please visit our [developers guide.](https://github.com/dotnet/machinelearning/blob/master/Documentation/project-docs/developer-guide.md) +To build ML.NET from source please visit our [developers guide.](Documentation/project-docs/developer-guide.md) Live build status is coming soon. ## Contributing -We welcome contributions! Please review our [contribution guide](https://github.com/dotnet/machinelearning/blob/master/CONTRIBUTING.md). +We welcome contributions! Please review our [contribution guide](CONTRIBUTING.md). ## Community @@ -53,9 +53,7 @@ For more information, see the [.NET Foundation Code of Conduct](https://dotnetfo ## Examples -Imagine you want to predict the sale price of a house. Given a large dataset of information about other houses, including their sale prices, you can use ML.NET to create and evaluate a model. Then, you can deploy the model with your app. - -Here's a different example, with code, to train a model to predict sentiment from text samples. (You can see the complete sample [here](https://github.com/dotnet/machinelearning/blob/master/test/Microsoft.ML.Tests/Scenarios/Scenario3_SentimentPrediction.cs)): +Here's an example of code to train a model to predict sentiment from text samples. (You can see the complete sample [here](https://github.com/dotnet/machinelearning/blob/master/test/Microsoft.ML.Tests/Scenarios/Scenario3_SentimentPrediction.cs)): ```C# var pipeline = new LearningPipeline(); From 2338344427df4e8307b73053c61dcbf05673d907 Mon Sep 17 00:00:00 2001 From: Dan Moseley Date: Mon, 7 May 2018 07:52:43 -0700 Subject: [PATCH 10/13] Update README.md --- README.md | 2 -- 1 file changed, 2 deletions(-) diff --git a/README.md b/README.md index 51e1cc90f5..4eb15cca97 100644 --- a/README.md +++ b/README.md @@ -12,8 +12,6 @@ With this first preview release ML.NET enables ML tasks like classification (e.g Along with these ML capabilities this first release of ML.NET also brings the first draft of .NET APIs for training models, using models for predictions, as well as the core components of this framework such as learning algorithms, transforms, and ML data structures. -ML.NET is first and foremost a framework which means it will be extensible to integrate popular ML libraries like TensorFlow, Accord.NET and CNTK. The design of the framework will prioritize usability, extensibility, and toolability, without sacrificing performance. - ## Installation ML.NET runs on Windows, Linux, and macOS - any platform where 64 bit [.NET Core](https://github.com/dotnet/core) or later is available. From 1693e4d4f699937228d26e7e5a3c8c7d38f3253e Mon Sep 17 00:00:00 2001 From: Shauheen Date: Mon, 7 May 2018 08:01:03 -0700 Subject: [PATCH 11/13] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 4eb15cca97..95c6ef3875 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,7 @@ [ML.NET](https://www.microsoft.com/net/learn/apps/machine-learning-and-ai/ml-dotnet) is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers. -ML.NET allows .NET developers to develop their own models and infuse custom ML into their applications without prior expertise in developing or tuning machine learning models. +ML.NET allows .NET developers to develop their own models and infuse custom ML into their applications without prior expertise in developing or tuning machine learning models, all without having to use multiple langugages and runtimes. ML.NET was originally developed in Microsoft Research and evolved into a significant framework over the last decade and is used across many product groups in Microsoft like Windows, Bing, PowerPoint, Excel and more. @@ -34,7 +34,7 @@ Or alternatively you can add the Microsoft.ML package from within Visual Studio' ## Building -To build ML.NET from source please visit our [developers guide.](Documentation/project-docs/developer-guide.md) +To build ML.NET from source please visit our [developers guide](Documentation/project-docs/developer-guide.md). Live build status is coming soon. From e8b37321f57d25086f2760a2bf693d6fd5389bbc Mon Sep 17 00:00:00 2001 From: Dan Moseley Date: Mon, 7 May 2018 08:05:05 -0700 Subject: [PATCH 12/13] Update README.md Remove misleading clause about languages. --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 95c6ef3875..7028726825 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,7 @@ [ML.NET](https://www.microsoft.com/net/learn/apps/machine-learning-and-ai/ml-dotnet) is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers. -ML.NET allows .NET developers to develop their own models and infuse custom ML into their applications without prior expertise in developing or tuning machine learning models, all without having to use multiple langugages and runtimes. +ML.NET allows .NET developers to develop their own models and infuse custom ML into their applications without prior expertise in developing or tuning machine learning models. ML.NET was originally developed in Microsoft Research and evolved into a significant framework over the last decade and is used across many product groups in Microsoft like Windows, Bing, PowerPoint, Excel and more. From b631ffbc52431696e05266309181c762a5c8bf1f Mon Sep 17 00:00:00 2001 From: Shauheen Date: Mon, 7 May 2018 08:12:38 -0700 Subject: [PATCH 13/13] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 7028726825..f0eb4218a9 100644 --- a/README.md +++ b/README.md @@ -4,7 +4,7 @@ [ML.NET](https://www.microsoft.com/net/learn/apps/machine-learning-and-ai/ml-dotnet) is a cross-platform open-source machine learning framework which makes machine learning accessible to .NET developers. -ML.NET allows .NET developers to develop their own models and infuse custom ML into their applications without prior expertise in developing or tuning machine learning models. +ML.NET allows .NET developers to develop their own models and infuse custom ML into their applications without prior expertise in developing or tuning machine learning models, all in .NET. ML.NET was originally developed in Microsoft Research and evolved into a significant framework over the last decade and is used across many product groups in Microsoft like Windows, Bing, PowerPoint, Excel and more.