dotnet/csharp-notebooks

Get started learning C# with C# notebooks powered by .NET Interactive and VS Code.

.NET Interactive Notebooks for C#

Welcome to the home of .NET interactive notebooks for C#!

How to Install

VS Code

1. Download the .NET Coding Pack for VS Code for Windows or macOS.
2. Install the Polyglot Notebooks extension.

C# 101

Download or clone this repo and open the csharp-101 folder in VS Code to get started with the C# 101 notebooks. Or, if you want just tap on one of the Notebook links below and automatically have it open in VS Code!

#	Topic	Notebook Link	Video Link	Documentation
1	Hello World	01 Notebook	01 Video	Intro to C#
2	The Basics of Strings	02 Notebook	02 Video	Intro to C#
3	Searching Strings	03 Notebook	03 Video	Intro to C#
4	Numbers and Integers Math	04 Notebook	04 Video	Numbers in C#
5	Numbers and Integer Precision	05 Notebook	05 Video	Numbers in C#
6	Numbers and Decimals	06 Notebook	06 Video	Numbers in C#
7	Branches (if)	07 Notebook	07 Video	Branches and Loops in C#
8	What Are Loops?	08 Notebook	08 Video	Branches and Loops in C#
9	Combining Branches and Loops	09 Notebook	09 Video	Branches and Loops in C#
10	Arrays, Lists, and Collections	10 Notebook	10 Video	Arrays, Lists, and Collections in C#
11	Search, Sort, and Index Lists	11 Notebook	11 Video	Arrays, Lists, and Collections in C#
12	Lists of Other Types	12 Notebook	12 Video	Arrays, Lists, and Collections in C#
13	Objects and Classes	13 Notebook	13 Video	Object Oriented Coding in C#
14	Methods and Members	14 Notebook	14 Video	Object Oriented Coding in C#
15	Methods and Exceptions	15 Notebook	15 Video	Object Oriented Coding in C#

Machine Learning

Download or clone this repo and open the machine-learning folder to get started with the machine-learning notebooks.

Getting Started Series

#	Topic	Notebook Link
1	Intro to Machine Learning	01 Notebook
2	Data Prep and Feature Engineering	02 Notebook
3	Training and AutoML	03 Notebook
4	Model Evaluation	04 Notebook
5	AutoML Sweepable API	05 Notebook
6	AutoML Tuners	06 Notebook

End to End (E2E) Notebooks - examples of the entire ML process.

#	Topic	Github Link
E2E	Classification using AutoML (Iris Dataset)	Iris E2E AutoML
E2E	Forecasting using Regression (Luna Dataset)	Luna E2E Regression
E2E	Forecasting using SSA (Luna Dataset)	Luna E2E SSA
E2E	Regression using AutoML (Taxi Dataset)	Taxi E2E AutoML
E2E	Text Classification API (Yelp Dataset)	Text Classification API

Reference Notebooks

#	Topic	Github Link
REF	Data Processing with DataFrame	Data Frame
REF	Graphs and Visualizations	Visualizations
REF	Kaggle Competitions (Titanic Dataset)	Kaggle
REF	AutoML Search Space	AutoML Search Space

.NET Foundation

.NET Interative Notebooks for C# is a .NET Foundation project.

There are many .NET related projects on GitHub.

• .NET home repo - links to 100s of .NET projects, from Microsoft and the community.
• ASP.NET Core home - the best place to start learning about ASP.NET Core.

This project has adopted the code of conduct defined by the Contributor Covenant to clarify expected behavior in our community. For more information, see the .NET Foundation Code of Conduct.

License

.NET (including the csharp-notebooks repo) is licensed under the MIT license.

csharp-notebooks's Issues

Getting started with .NET.dib mispelling

Hi All,

this notebook from this link - https://ntbk.io/csharp101-notebook01 , has a mispelling in the description of the For-Each Loops,

Can't the book on the repo so cant fix it myself,

Thanks

Link to Marketplace no longer finds Notebook extension to install

Did you remove The Notebook extension for Visual Studio 2022 from the Marketplace? Where to get the latest version of the C# Notebook Extension for Visual Studio 2022?

Are ML.NET notebooks using non-public #r nuget references?

Are the ML.NET notebooks using non-public preview nugets?

I tried to run the first ML.NET notebook 01- Intro to ... I get the following error:

#r "nuget: Microsoft.ML, 2.0.0-preview.22356.1"

C:\Users\nicho\AppData\Local\Temp\nuget\20332--ab38aca3-7c58-4abd-98f6-0079cd1c2c87\Project.fsproj : error NU1102: Unable to find package Microsoft.ML with version (>= 2.0.0-preview.22356.1)
C:\Users\nicho\AppData\Local\Temp\nuget\20332--ab38aca3-7c58-4abd-98f6-0079cd1c2c87\Project.fsproj : error NU1102:   - Found 33 version(s) in nuget.org [ Nearest version: 2.0.0-preview.22313.1 ]
C:\Users\nicho\AppData\Local\Temp\nuget\20332--ab38aca3-7c58-4abd-98f6-0079cd1c2c87\Project.fsproj : error NU1102:   - Found 0 version(s) in Microsoft Visual Studio Offline Packages

This is the latest on nuget.org: #r "nuget: Microsoft.ML, 2.0.0-preview.22313.1"

ML Notebooks should use Plotly.NET

Replace XPlot with Plotly.NET.

Blocked on..

• Plotly.NET getting signed. plotly/Plotly.NET#175
• Also waiting on C# improvements plotly/Plotly.NET#285

Translate to Local Language

I have an idea to translate this into Sinhalese (Sri Lanka).

If I create a new branch on my local repo, will it be merged as a separate branch at the base?

Thanks

Download dataset automatically

When using a ML notebook, it should download the dataset from github if it's not available.

Alien translator: modify a collection in a foreach loop

The last code block of the Alien translator notebook lacks clarity.

Since you use the same collection variable before and after the foreach loop, it seems like you want the "student" to modify the collection in-place, which is not possible using a foreach loop.

Since the notebook is aimed at new C# programmers, it might be better to hint at a clearer pattern.

Maybe I'm missing something?

ML Notebook improvements

Thanks @andrasfuchs for trying out the notebooks and providing feedback:

This feedback is specific to the Training and AutoML notebook, but it's also good feedback in general to follow across notebooks.

• The capitalization of "ML.NET" is not consistent in the document

• The "This notebook is under active development" is barely visible with Visual Studio's dark theme
  

• The tutorial is easy to follow, I just missed the links to the different classes and methods (like .Fit, IDataView, Regression.Trainers, TrainTestSplit, etc.), because although they are familiar it would be nice to have a way to jump to that particular class or method to investigate it further. F1 doesn't seem to work as it normally does when I browse my own code.

• It would have been a little better if the sample datasets had more than one feature columns, just to see how Transforms.Concatenate should look like in that case

• In the "Use AutoML..." section when I run the code, it only showed a grey rectangle while it was running, and when it finished it remained a grey and made all the other previous outputs shown as grey rectangles.

  

  When I closed the file, reopened it and clicked "Run All", I got the following exception:

  

E2E regression with Taxi is not rendering on github

When I click here I see

Improve experience for deep-linking into Visual Studio/Visual Studio Code

Just noticed a small inconsistency, not sure if it's intentional.

When I click on C# 101 notebook links, they open .net interactive in vs code (with python set ast the kernel). When I click the ML.NET notebooks they open in visual studio 2022.

Add nav menu icon and make nav visible when selected

ML Notebook cleanup

• Ensure Model Builder references are removed.
• Link to appropriate reference sections
• Spell check
• Content
• Remove "Unknown => " from the pipeline. Rename "Pipeline" to "Trainer". Add parameters column.

Local and Authenticated NuGet source break Package Restore

The machine learning notebooks reference Microsoft.ML version 2.0.0-preview.22356.1 from a private Azure DevOps server. This preview version of the Microsoft.ML package is not available from nuget.org making it hard to run the notebooks.

PackageManagement Error 3217 Invalid URI: The format of the URI could not be determined.

What is the reason to support two versions of notebooks?

I had forked this repository and started to translate it to Ukrainian (the first notebook is done).
But there are two versions of each notebook (dib and ipynb). I don't want to double my work.
Which one is better to choose?
What is the reason to support two versions of notebooks?

ML Notebook Enhancements

• Add reference documentation links to classes like transforms and trainers. (i.e. LightGBM)
• Include parameter names in method calls. (i.e. mlContext.Data.TrainTestSplit(data,testFraction: 0.2))
• Use real data for examples. It makes it easier to understand the problem that's being solved opposed to randomly generated data.
• Watch for code comments. Instead of embedding them in the code, promote them to text in a Markdown cell.

---

• Put related code together. Break up cells containing large chunks of code and add Markdown cells explaining what each of the cells is doing.

Example

Original

var context =new MLContext(seed: 1);
var pipeline = context.Transforms.Concatenate("Features", "X")
  .Append(context.Auto().Regression("y", useLbfgs: false, useSdca: false, useFastForest: false));

var monitor = new NotebookMonitor();
var experiment = context.Auto().CreateExperiment();
experiment.SetPipeline(pipeline)
  .SetEvaluateMetric(RegressionMetric.RootMeanSquaredError, "y")
  .SetTrainingTimeInSeconds(30)
  .SetDataset(trainTestSplit.TrainSet, trainTestSplit.TestSet)
  .SetMonitor(monitor);

// Configure Visualizer			
monitor.SetUpdate(monitor.Display());

var res = await experiment.RunAsync();

Update

Initialize MLContext

MLContext is the starting point for all ML.NET applications.

var context =new MLContext(seed: 1);

Define training pipeline

• Concatenate: Takes the input column X and creates a feature vector in the Features column.
• Regression: Defines the task AutoML needs to find the best algorithm and hyperparameters for. In this case, Lbfgs, Sdca, and FastForest algorithms won't be explored since their respective parameters are set to false.

var pipeline = context.Transforms.Concatenate("Features", "X")
      .Append(context.Auto().Regression("y", useLbfgs: false, useSdca: false, useFastForest: false));

Initialize Monitor

The notebook monitor provides visualizations of the training progress as AutoML tries to find the best model for your data.

var monitor = new NotebookMonitor();

Initialize AutoML Experiment

An AutoML experiment is a collection of trials in which algorithms are explored.

var experiment = context.Auto().CreateExperiment();

Configure AutoML Experiment

The AutoML experiment tries to find the best algorithm using an evaluation metric. In this case, the evaluation metric selected is Root Mean Squared Error. The goal is to find the optimal evaluation metric in the provided training time which is set to 30 seconds. The longer you train, the more algorithms and hyperparameters AutoML is able to explore. The training set is the dataset that AutoML uses to train the model and the test set is used to calculate the evaluation metric to see how well a particular model selected by AutoML performs.

experiment.SetPipeline(pipeline)
        .SetEvaluateMetric(RegressionMetric.RootMeanSquaredError, "y")
        .SetTrainingTimeInSeconds(30)
        .SetDataset(trainTestSplit.TrainSet, trainTestSplit.TestSet)
        .SetMonitor(monitor);

Set monitor to display

monitor.SetUpdate(monitor.Display());

Run AutoML experiment

var res = await experiment.RunAsync();

---

• NotebookMonitor: Display evaluation metric for best trial, active trial, and y-axis on graph.
• When adding feeds, add link to document on how to reference them in VS / dotnet CLI
• When installing NuGet packages that are not part of the BCL, list them in a Markdown cell where the packages are installed, and add a link to NuGet. (i.e. Microsoft.ML).

Themes support

This is how it looks in the "Dark" theme

User Input

Within these interactive notebooks, I am unable to find any examples on how to get a user's input? As I try Console.ReadLine() it proceeds to execute the next line of code.

Example:
string []answer = new string[10];

for(int i = 0; i < answer.Length; i++)
{
answer[i]= Console.ReadLine();
}

With this code, the cell keeps running for me with no prompt (like with Python) to enter an input.

Getting alot of Errors: "Kernel Failed To Start."

Have VS2022 installed, installed the Notebook editor extension and just opened the getting started folder and getting the following
I was able to build C# Projects with my VS2022 and also C# Interactive windows work in VS2022

Kernel Failed To Start.
Cannot find a tool in the manifest file that has a command named 'dotnet-interactive'.

error: Cannot find a tool in the manifest file that has a command named 'dotnet-interactive'. 
    at StreamJsonRpc.JsonRpc.<InvokeCoreAsync>d__143`1.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
   at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()
   at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)
   at Microsoft.VisualStudio.Notebook.Utils.DetectKernelStatusService.<ExecuteTaskAsync>d__3.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
   at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()
   at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)
   at Microsoft.VisualStudio.Notebook.Utils.RepeatedTimeTaskService.<>c__DisplayClass7_0.<<ExecuteAsync>b__1>d.MoveNext()
error: Cannot find a tool in the manifest file that has a command named 'dotnet-interactive'. 
    at StreamJsonRpc.JsonRpc.<InvokeCoreAsync>d__143`1.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
   at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()
   at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)
   at Microsoft.VisualStudio.Notebook.Utils.DetectKernelStatusService.<ExecuteTaskAsync>d__3.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
[...]

Machine Learning

Add H1 heading to machine learning notebooks with title of the notebook

ML Notebook consumes all the available memory, forcing Windows to close processes

The Training and AutoML notebook is able to consume a lot of memory, causing to hang or crash other processes.

Strangely enough, it usually works fine if you run the notebook only once. So to reproduce the problem, you should:

1. Open Windows Task Manager, and check your memory usage
2. Open Training and AutoML notebook
   
3. Run it's snippets one by one, but stop at "Use AutoML to simplify trainer selection and hyper-parameter optimization."
   
4. Run the "Use AutoML to simplify trainer selection and hyper-parameter optimization" code.
   
5. Sometimes it works fine, but last time at this point my system hang and terminated some VS processes and closed my browser unexpectedly. Memory consumption dropped back to ~950 MBs, and the notebook got into a seemingly endless loop of "Starting Kernel".
   
6. When I tried to re-run the "Use AutoML to simplify trainer selection and hyper-parameter optimization" code snippet again, I got the following exception, repeating over and over:
   

error: The JSON-RPC connection with the remote party was lost before the request could complete. 
    at StreamJsonRpc.JsonRpc.<InvokeCoreAsync>d__154.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
   at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()
   at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)
   at StreamJsonRpc.JsonRpc.<InvokeCoreAsync>d__143`1.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
   at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()
   at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)
   at Microsoft.VisualStudio.Notebook.Utils.DetectKernelStatusService.<ExecuteTaskAsync>d__3.MoveNext()
--- End of stack trace from previous location where exception was thrown ---
   at System.Runtime.ExceptionServices.ExceptionDispatchInfo.Throw()
   at System.Runtime.CompilerServices.TaskAwaiter.HandleNonSuccessAndDebuggerNotification(Task task)
   at Microsoft.VisualStudio.Notebook.Utils.RepeatedTimeTaskService.<>c__DisplayClass7_0.<<ExecuteAsync>b__1>d.MoveNext()

7. If you could run the notebook without issues, try to re-run the "Use AutoML to simplify trainer selection and hyper-parameter optimization" code many times, it is inconsistent on my machine as well.

E2E-Classification with Iris Dataset.ipynb -> 'NotebookMonitor' could not be found

I tried running the "machine-learning/E2E-Classification with Iris Dataset.ipynb" file, and received the following error:

The type or namespace name 'NotebookMonitor' could not be found (are you missing a using directive or an assembly reference?)

Versions of things:

• .NET 7 SDK: 7.0.401
• .NET Version: 7.0.11
• VS Code: 1.82.2
• Polyglot Notebooks: v1.0.4461041 (pre-release)

Tried searching for that object on the internet and it's used around this repo, but for me, it doesn't work in any of the. I also tried changing the Polyglot extension to "Release" and that didn't do anything. I also tried upgrading Microsoft.ML and Microsoft.ML.AutoML to the most recent versions (2.0.1, 0.20.1, respectively) and that didn't work.

I was able to get around the error by just removing the monitor, but that's not fun!

E2E-Classification with Iris Dataset.ipynb

E2E-Forecasting using Autoregressive with Luna Dataset.ipynb

Add link to the github location of the notebook

The readme.md links that automatically open visual studio is a great experience if you have the notebook extension installed. However, if you don't have the notebook extension installed when you first come to the site (👋 ), then nothing happens when you click on the link and it seems like something is broken. I eventually saw the "Links below require Visual Studio 2022 and Notebook Editor Extension" but it was not immediate.

Would it make sense to also add a link to the github URL of the notebook?

Something along these lines below might be more obvious. I don't know what to call things, the main point is two links:

#	Topic	Notebook link (requires VS and notebook extension)	Github link
1	Intro to Machine Learning	01 Notebook	01 Notebook

Or..

#	Topic	Notebook link
1	Intro to Machine Learning	01 Notebook / Github version