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Merge pull request #34 from JakeRadMSFT/main
Update ReadMe Links to add Machine Learning
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README.md

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@@ -4,9 +4,14 @@ Welcome to the home of .NET interactive notebooks for C#!
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## How to Install
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### VS Code
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1. Download the .NET Coding Pack for VS Code for [Windows](https://aka.ms/dotnet-coding-pack-win) or [macOS](https://aka.ms/dotnet-coding-pack-mac).
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2. Install the [.NET Interactive Notebooks](https://marketplace.visualstudio.com/items?itemName=ms-dotnettools.dotnet-interactive-vscode) extension.
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### Visual Studio
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1. Download and install [Visual Studio 2022](https://visualstudio.microsoft.com/downloads/)
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2. Download and install [Notebook Editor Extension](https://marketplace.visualstudio.com/items?itemName=MLNET.notebook)
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For more information and resources, visit [Learn to code C#](https://dotnet.microsoft.com/learntocode).
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## C# 101
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14 | Methods and Members | [14 Notebook](https://ntbk.io/csharp101-notebook14) | [14 Video](https://www.youtube.com/watch?v=xLhm3bEG__c&list=PLdo4fOcmZ0oVxKLQCHpiUWun7vlJJvUiN&index=17) | [Object Oriented Coding in C#](https://docs.microsoft.com/dotnet/csharp/fundamentals/tutorials/classes?WT.mc_id=csharpnotebook-35129-website)
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15 | Methods and Exceptions | [15 Notebook](https://ntbk.io/csharp101-notebook15) | [15 Video](https://www.youtube.com/watch?v=8YsoBBiVVzQ&list=PLdo4fOcmZ0oVxKLQCHpiUWun7vlJJvUiN&index=18) | [Object Oriented Coding in C#](https://docs.microsoft.com/dotnet/csharp/fundamentals/tutorials/classes?WT.mc_id=csharpnotebook-35129-website)
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## Machine Learning
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Download or clone this repo and open the `machine-learning` folder in Visual Studio 2022 to get started with the machine-learning notebooks. Or, if you want just tap on one of the Notebook links below and automatically have it open in Visual Studio!
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**Links below require [Visual Studio 2022](https://visualstudio.microsoft.com/downloads/) and [Notebook Editor Extension](https://marketplace.visualstudio.com/items?itemName=MLNET.notebook) 0.3.4 or greater**
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### Getting Started Series
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| # | Topic | Notebook Link |
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|---|--------------------------------------------|-----------------------|
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1 | Intro to Machine Learning | [01 Notebook](https://ntbk.io/ml-01-intro)
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2 | Data Prep and Feature Engineering | [02 Notebook](https://ntbk.io/ml-02-data)
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3 | Training and AutoML | [03 Notebook](https://ntbk.io/ml-03-training)
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4 | Model Evaluation | [04 Notebook](https://ntbk.io/ml-04-evaluation)
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### Reference Notebooks
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| # | Topic | Notebook Link |
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|---|--------------------------------------------|-----------------------|
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REF | Data Processing with DataFrame |[Data Frame](https://ntbk.io/ml-ref-data-frame)
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REF | Graphs and Visualizations |[Visualizations](https://ntbk.io/ml-ref-visualizations)
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REF | Kaggle Competitions (Titanic Dataset) |[Kaggle](https://ntbk.io/ml-ref-kaggle-titanic)
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### End to End (E2E) Notebooks - for examples of the entire ML process.
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| # | Topic | Notebook Link |
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|---|--------------------------------------------|-----------------------|
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E2E | Classification using AutoML (Iris Dataset) | [Iris E2E AutoML](https://ntbk.io/ml-e2e-iris)
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E2E | Forecasting using Regression (Luna Dataset)| [Lune E2E Regression](https://ntbk.io/ml-e2e-luna-regression)
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E2E | Forecasting using SSA (Luna Dataset) | [Lune E2E SSA](https://ntbk.io/ml-e2e-luna-ssa)
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E2E | Regression using AutoML (Taxi Dataset) | [Taxi E2E AutoML](https://ntbk.io/ml-e2e-taxi)
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## .NET Foundation
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.NET Interative Notebooks for C# is a [.NET Foundation](https://www.dotnetfoundation.org/projects) project.

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