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.

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?

Replace XPlot with Plotly.NET.

Blocked on..

• Plotly.NET getting signed. https://github.com/plotly/Plotly.NET/issues/175
• Also waiting on C# improvements https://github.com/plotly/Plotly.NET/issues/285

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?

I'm not happy with this yet, but this is the shape of what I'm doing. I'm going to make more edits to the copy to make it less awkward, and add more description.

Simple data processing example. This examples shows how to...

• Replace null values.
• Remove rows with null values.
• Combine two identical data sources.
• Transform columns into different formats.
• Join two data sources.

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"

Description

Dib isn’t as common of a notebook file type as ipynb. Converting to ipynb allows these notebooks to work with VS, VS Code, and everywhere else ipynb is supported.

• 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).

Update Alien Example to use for loop instead of for-each ... so words array can be updated in-place.

@katiesavage @jamesmontemagno Is this how it was intended to be?

Resolves #62

You can view the updated Notebook here: https://github.com/dotnet/csharp-notebooks/blob/32bc3eb9f1a2535d212506393e0a2dc561974693/csharp-scenarios/01-Alien-Translator.ipynb

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?

• Taxi Notebook had an error when it uses a OneHotHashEncoder @LittleLittleCloud ... can we filter that out from Auto-Featurizer? OneHotEncoder works fine.
• DataFrame/DataPrep notebook wasn't downloading one of it's data files.

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.