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Overview

.NET Interactive Notebooks for C#

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

How to Install

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

For more information and resources, visit Learn to code C#.

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#

.NET Foundation

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

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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.

Owner
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GitHub Repository
Repo for our ICML21 paper Unsupervised Learning of Visual 3D Keypoints for Control

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Code for the Paper: Alexandra Lindt and Emiel Hoogeboom.

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Code for the paper "Graph Attention Tracking". (CVPR2021)

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122 Dec 24, 2022
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HEAM: High-Efficiency Approximate Multiplier Optimization for Deep Neural Networks

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Official code for MPG2: Multi-attribute Pizza Generator: Cross-domain Attribute Control with Conditional StyleGAN

This is the official code for Multi-attribute Pizza Generator (MPG2): Cross-domain Attribute Control with Conditional StyleGAN. Paper Demo Setup Envir

Fangda Han 5 Sep 01, 2022
Pytorch implementation of Zero-DCE++

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Chongyi Li 157 Dec 23, 2022
NOMAD - A blackbox optimization software

################################################################################### #

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YOLOv5 + ROS2 object detection package

YOLOv5-ROS YOLOv5 + ROS2 object detection package This program changes the input of detect.py (ultralytics/yolov5) to sensor_msgs/Image of ROS2. Requi

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248 Dec 25, 2022
https://arxiv.org/abs/2102.11005

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Instance Segmentation in 3D Scenes using Semantic Superpoint Tree Networks

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