Machine Learning and AI topics

How GitHub Copilot Helps with Test-Driven Development (TDD)

JohnNaguib — Wed, 20 Aug 2025 14:19:05 GMT

Test-Driven Development (TDD) has been a cornerstone of modern software engineering for decades. By writing tests before implementing functionality, developers ensure better design, maintainability, and fewer bugs. But while TDD is powerful, it can sometimes feel slow or cumbersome, especially when setting up repetitive test structures or boilerplate code.

This is where GitHub Copilot, the AI-powered coding assistant, becomes a valuable partner. It doesn’t replace the discipline of TDD, but it can accelerate the process and help developers stay in the flow.

https://dellenny.com/how-github-copilot-helps-with-test-driven-development-tdd/

Boosting Productivity with GitHub Copilot Real-World .NET Coding Examples

JohnNaguib — Wed, 20 Aug 2025 14:18:35 GMT

Software development in the .NET ecosystem is powerful, but projects can quickly get bogged down with boilerplate code, repetitive tasks, and lengthy setup. This is where GitHub Copilot comes in. Acting as your AI pair programmer inside Visual Studio or VS Code, Copilot suggests context-aware code snippets, tests, and even full method implementations.

Let’s dive into real-world .NET coding examples that highlight how Copilot can make you more productive.

https://dellenny.com/boosting-productivity-with-github-copilot-real-world-net-coding-examples/

ML.NET Sentence Similarity scenario questions

tec_mlnetuser — Sat, 11 Jan 2025 01:00:00 GMT

How do you make the ML.NET Sentence Similarity scenario context-aware? I'm using the Model Builder to train, evaluate, and consume the model. I would like to create a context prior to comparing sentences. Is this possible? Is there a way to introduce this in the pipeline?
Does a model in ML.NET rely entirely on the training dataset? Is there a pre-trained dataset behind the scenarios?
Training a Sentence Similarity model only works when you use validation dataset. Using Cross validation or the Split option always returns this error.
"Training time finished without completing a successful trial. Either no trial completed or the metric for all completed trials are NaN or Infinity"
Is this a bug?

How do I create a custom model not possible with the ML.net model builder?

levicc00123 — Mon, 11 Nov 2024 21:23:47 GMT

I want to create a ML that ranks news articles based on how positive/negative they are, but Bing and other sources haven't given me anything I can work with.

chest Xray prediction using NIH data set

Adebowale985 — Thu, 02 Nov 2023 03:21:18 GMT

please I need help I'm working on chest xray prediction using an NIH data set and also building a mobile app for deployment

Gpt3 model for spelling correction is not working for every sentances

Lakshmi_145 — Wed, 18 Oct 2023 17:41:28 GMT

I have used GPT-3 model for correcting the spelling mistakes in questions we are providing to the bot.

Used the below code for connecting to model,

GPT-3 provides the corrected text for few words. But it does not provide the corrected text for long sentences.

ML.Net CLI Example Fails

DaleC975 — Thu, 20 Apr 2023 04:56:56 GMT

On following the instructions here:

https://learn.microsoft.com/en-us/dotnet/machine-learning/tutorials/sentiment-analysis-cli

at this step

mlnet classification --dataset "yelp_labelled.txt" --label-col 1 --has-header false --train-time 10

I get this error:

System.InvalidOperationException: Unable to resolve service for type 'Microsoft.ML.AutoML.IDatasetManager' while attempting to activate 'Microsoft.ML.AutoML.SweepablePipelineRunner'.
at Microsoft.Extensions.DependencyInjection.ServiceLookup.CallSiteFactory.CreateArgumentCallSites(Type implementationType, CallSiteChain callSiteChain, ParameterInfo[] parameters, Boolean throwIfCallSiteNotFound)
at Microsoft.Extensions.DependencyInjection.ServiceLookup.CallSiteFactory.CreateConstructorCallSite(ResultCache lifetime, Type serviceType, Type implementationType, CallSiteChain callSiteChain)
...

...

mlnet --version says 16.15.0

Anyone know what's wrong?

How to create mini search engine by using ML.Net with c#?

Maifs — Sat, 15 Apr 2023 11:39:23 GMT

I have some medicine names in Sql server database table.

Now I want to create some feature by using ML.Net c#? I am totally new to ML.NET.

What I want is that ASAP user try to write anything in my textbox (.Aspx page),

my ML.Net feature should suggest the user.

for example : user write "penadol 40 mg" or "panadl" or "Pandole" and there can be some other patterns as well.

My ML.Net logic would suggest the user "Panadol" by finding from the database.

Something, very similar to English spell check feature or mini search engine

Now I am going to tell you about the structure of development. Currently , my application is developed in aspx ,

As soon as user 'll enter some medicine name in the textbox,

an ajax request 'll go to the server and 'll display the suggested medicine list.

Ajax call can be requested to an API which 'll be used this ML.NET developed feature.

And this API can be developed in any .Net/ .Net Core Framework .

Please guide me . Thank you very much.

Please ask anything if want to further know anything from me.

Dataset for toxic comments detection

AndiDendy_1234 — Sat, 25 Mar 2023 20:03:36 GMT

Hello there,

I have a website that contains a list of resources (basically other websites). Users can leave their reviews for each resource, a review consists of Title, Text and Rate (number 0-5). I want to implement toxic and offensive reviews detection using ML .Net. I don't have experience of work with ML, but I've checked intro course from MS (https://dotnet.microsoft.com/en-us/learn/ml-dotnet/get-started-tutorial/intro) and as far as I understand I need a dataset with textual reviews and their classes (like 0 - for toxic and 1 - for normal).

I will be thankful if you advise my further steps, share tutorials etc.
Also can you advise such datasets? Or provide a link to github repo with working code?
Thanks.

Consume Azure Custom Vision ONNX Models with ML.NET

LuisQuintanilla — Mon, 13 Mar 2023 19:26:35 GMT

Azure Custom Vision is an image recognition service that lets you build, deploy, and improve your own computer vision models. Custom Vision allows you to specify your own labels and train custom machine models using your data. Custom Vision supports training models for the following tasks:

Once you've trained a model, Custom Vision provides you with a variety of formats to export and deploy your model to.

One of those formats is the Open Neural Network Exchange (ONNX).

ONNX is an open-source format to represent AI models. ONNX models can be used to make predictions with the help of the ONNX Runtime (ORT). The ORT is a runtime for ONNX models which provides an interface for accelerating the consumption / inferencing of machine learning models, integrating with hardware-specific libraries, and sharing models across programming languages and frameworks like PyTorch, Tensorflow / Keras, scikit-learn, Windows ML, ML.NET, and others.

ML.NET is an open-source, cross-platform machine learning framework for .NET developers. ML.NET provides a set of APIs that build on the ONNX Runtime. That means you can take models you've exported from Custom Vision and use them inside your .NET applications.

Get started with Custom Vision and ML.NET

To get started using Custom Vision models with ML.NET

Train an image classification or object detection model.
Export your model to ONNX
Use and reference these sample applications which show how to build an ML.NET pipeline that consumes a Custom Vision ONNX model.

Resources

dotnet Amsterdam Meetup Recording - January 11 2023 - Daniel Costea - What's new in ML.NET 2.0

LuisQuintanilla — Mon, 30 Jan 2023 20:34:53 GMT

Model Builder - Image classification - shifting from CPU to GPU

FaithlessDbo — Sun, 29 Jan 2023 12:10:22 GMT

I'm trying to classify images based on 14 different categories. Currently I have about 40.000 images, but I'm planning to add more to try and get a better dataset.

Initially I have trained my dataset with my CPU and has pretty decent accuracy (90-98% in most cases), but the training and prediction speed is rather slow. Now I'm trying to use my GPU to speed up this task. The speed is amazing when it's training through the model builder, however the accuracy is terrible. I get about 8% accuracy and the expected category isn't even listed in some cases.

The only thing I changed is the CPU to GPU in the Model Builder GUI. Is there something I'm missing here? Do I require even more images to get the same results with my GPU vs my CPU?

I'm at a loss here so any help would be really appreciated!

Machine Learning Community Standup - January 18, 2023

LuisQuintanilla — Wed, 18 Jan 2023 17:58:55 GMT

Topic: New Year, New Releases

Recording

Community Links

Resources

Feedback

We want to hear from you. Do you have topics you'd like to hear more about or have ideas on how we can improve the show? Take a few minutes to fill out our feedback form.

Stay Connected

Join the Virtual ML.NET Community Discord and the #machine-learning channel on the .NET Development Discord.

Find recordings from previous shows on .NET Live TV

New to AI and ML

Dnck-master160 — Wed, 04 Jan 2023 14:28:44 GMT

Hi All,

Im new to AI and Ml.

looking for some help for my first project which is a given text of 1 - 5 rows with a person information

and i should extract the person first name and last name) and age and disregard all other info.

Thanks for helping.

an example of text would be:

This guy Alexander Jordan was 50 last year

His date of birth is 17/10/1962.

He lives in N.Y.

He has two daugter

How to make the prediction value to be within the range?

alex4998 — Tue, 25 Oct 2022 14:51:44 GMT

First of all, my question is related to ML.NET but I'm also curious if there are technics available in other frameworks if ML.NET does not allow it.

I have an input vector of floats containing 220 items and a float label which is a value in the range of -1 .. 1 as training data. I have hundreds of thousands of rows of the data I run through the learning pipeline. So far, I tried only fast tree algorithm. One thing I'd like to ask what algorithm do you think will be the best for this type of data?

Then I create a prediction engine, pass vectors of 220 float values and obtain predicted values. In most cases the predicted value is within the range of -1 .. 1 as I expect but rather often the value can be 1.23 or -1.12 or any other value outside of that range but I didn't see a value over 1.5 or -1.5 yet. Is there a way to specify in the prediction engine or in the model that I train that the predicted value must be in the range of -1 .. 1?

Machine Learning Community Standup | August 17, 2022

LuisQuintanilla — Wed, 17 Aug 2022 17:52:21 GMT

Topic: Introducing SynapseML

Recording

Community Links

Resources

Feedback

We want to hear from you. Do you have topics you'd like to hear more about or have ideas on how we can improve the show? Take a few minutes to fill out our feedback form.

Stay Connected

Join the Virtual ML.NET Community Discord and the #machine-learning channel on the .NET Development Discord.

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Machine Learning Community Standup | June 22, 2022

LuisQuintanilla — Wed, 22 Jun 2022 18:00:34 GMT

Topic: Text Classification, AutoML, and Notebooks

Recording

Community Links

Feedback

We want to hear from you. Do you have topics you'd like to hear more about or have ideas on how we can improve the show? Take a few minutes to fill out our feedback form.

Stay Connected

Join the Virtual ML.NET Community Discord and the #machine-learning channel on the .NET Development Discord.

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Train Machine Learning Models with ML.NET Model Builder on ARM64

LuisQuintanilla — Wed, 15 Jun 2022 20:19:37 GMT

Visual Studio 2022 17.3 Preview 2 is now available as a native ARM64 application on Windows 11. This is the first version of Visual Studio that natively supports building and debugging ARM64 apps on ARM-based processors. .NET workloads are one of the prioritized workloads.

What is Model Builder?

Model Builder is a Visual Studio extension that uses ML.NET, an open-source, cross-platform machine learning framework for .NET developers to train and deploy custom machine learning models into .NET apps.

Get started

To get started with Model Builder on ARM64 devices:

Note: For image classification scenarios, we recommend using Azure since it's not supported for local environments on ARM devices. For more information, see the tutorial on how to train an image classification model in Azure using Model Builder.

We want to hear from you

Let us know about your experiences. If you have any feedback or issues running Model Builder on ARM, file an issue in the dotnet/machinelearning-modelbuilder GitHub repository.

Announcing .NET Machine Learning Notebook Series

LuisQuintanilla — Wed, 01 Jun 2022 18:44:08 GMT

.NET Interactive Notebooks

.NET Interactive takes the power of .NET and embeds it into interactive experiences. One of these interactive experiences is notebooks. Notebooks are files that contain executable code, visualizations, and raw text all within the same file. Interactive notebooks are used extensively in data science and machine learning. They are great for data exploration and preparation, experimentation, model explainability, and education.

Since the announcement of the Notebook Editor extension in Visual Studio last October, we've been constantly working to improve the experience. We've continuously made stability and performance improvements to the extension and in our most recent release we enabled keyboard shortcuts and deep-linking capabilities to automatically open notebooks in Visual Studio.

To go along with these updates and showcase the power of notebooks for data science and machine learning applications, we've put together a series of notebooks that cover getting started and end-to-end machine learning scenarios. This is the first version of these notebooks and we plan to continue iterating on them.

How can you get started?

On a recent episode of VS Toolbox Live, we provided an overview of notebooks in Visual Studio and the machine learning notebook series. Take a look at that recording to get a sense of what notebooks are and how they can be useful for your workflows.

When you're ready to get started exploring the notebooks yourself:

Download and install the latest version of Visual Studio.
Download and install the latest version of the Visual Studio Notebook Editor extension.
Download or clone the dotnet/csharp-notebooks GitHub repository and open the machine-learning directory in Visual Studio.

Alternatively if you're on Mac or Linux, use Visual Studio Code and the .NET Interactive Notebooks extension.

We want to hear from you

Let us know about your experiences:

Provide suggestions on notebook topics in the dotnet/csharp-notebooks GitHub repository.
Issues with the .NET Interactive extensions? File an issue in the dotnet/interactive GitHub repository.

AutoML

__James__ — Wed, 25 May 2022 14:58:19 GMT

Hi, I was looking for some answers on training.

I like how the AutoML works, especially when the parameters are auto tweaked for a better fit.

Is there a way to select a specific algorithm and have the automl iterate over that for X minutes, like the autoML wizard but for a specific algorithm?

thank you