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

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.

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.

Owner
.NET Platform
Home of the open source .NET platform
.NET Platform
Pytorch implement of 'Unmixing based PAN guided fusion network for hyperspectral imagery'

Pgnet There's a improved version compared with the publication in Tgrs with the modification in the deduction of the PDIN block: https://arxiv.org/abs

5 Jul 01, 2022
Pytorch domain adaptation package

DomainAdaptation This package is created to tackle the problem of domain shifts when dealing with two domains of different feature distributions. In d

Institute of Computational Perception 7 Oct 22, 2022
Implicit Deep Adaptive Design (iDAD)

Implicit Deep Adaptive Design (iDAD) This code supports the NeurIPS paper 'Implicit Deep Adaptive Design: Policy-Based Experimental Design without Lik

Desi 12 Aug 14, 2022
Tensorflow 2 implementations of the C-SimCLR and C-BYOL self-supervised visual representation methods from "Compressive Visual Representations" (NeurIPS 2021)

Compressive Visual Representations This repository contains the source code for our paper, Compressive Visual Representations. We developed informatio

Google Research 30 Nov 23, 2022
A PyTorch implementation of the paper "Semantic Image Synthesis via Adversarial Learning" in ICCV 2017

Semantic Image Synthesis via Adversarial Learning This is a PyTorch implementation of the paper Semantic Image Synthesis via Adversarial Learning. Req

Seonghyeon Nam 146 Nov 25, 2022
A new codebase for Group Activity Recognition. It contains codes for ICCV 2021 paper: Spatio-Temporal Dynamic Inference Network for Group Activity Recognition and some other methods.

Spatio-Temporal Dynamic Inference Network for Group Activity Recognition The source codes for ICCV2021 Paper: Spatio-Temporal Dynamic Inference Networ

40 Dec 12, 2022
a reimplementation of UnFlow in PyTorch that matches the official TensorFlow version

pytorch-unflow This is a personal reimplementation of UnFlow [1] using PyTorch. Should you be making use of this work, please cite the paper according

Simon Niklaus 134 Nov 20, 2022
YouRefIt: Embodied Reference Understanding with Language and Gesture

YouRefIt: Embodied Reference Understanding with Language and Gesture YouRefIt: Embodied Reference Understanding with Language and Gesture by Yixin Che

16 Jul 11, 2022
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

Ar-Ray 23 Dec 19, 2022
docTR by Mindee (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.

docTR by Mindee (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.

Mindee 1.5k Jan 01, 2023
Machine Unlearning with SISA

Machine Unlearning with SISA Lucas Bourtoule, Varun Chandrasekaran, Christopher Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, N

CleverHans Lab 70 Jan 01, 2023
Effective Use of Transformer Networks for Entity Tracking

Effective Use of Transformer Networks for Entity Tracking (EMNLP19) This is a PyTorch implementation of our EMNLP paper on the effectiveness of pre-tr

5 Nov 06, 2021
Relative Human dataset, CVPR 2022

Relative Human (RH) contains multi-person in-the-wild RGB images with rich human annotations, including: Depth layers (DLs): relative depth relationsh

Yu Sun 112 Dec 02, 2022
Multi-Scale Aligned Distillation for Low-Resolution Detection (CVPR2021)

MSAD Multi-Scale Aligned Distillation for Low-Resolution Detection Lu Qi*, Jason Kuen*, Jiuxiang Gu, Zhe Lin, Yi Wang, Yukang Chen, Yanwei Li, Jiaya J

Jia Research Lab 115 Dec 23, 2022
Homepage of paper: Paint Transformer: Feed Forward Neural Painting with Stroke Prediction, ICCV 2021.

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction [Paper] [Official Paddle Implementation] [Huggingface Gradio Demo] [Unofficial

442 Dec 16, 2022
Hough Transform and Hough Line Transform Using OpenCV

Hough transform is a feature extraction method for detecting simple shapes such as circles, lines, etc in an image. Hough Transform and Hough Line Transform is implemented in OpenCV with two methods;

Happy N. Monday 3 Feb 15, 2022
Python Implementation of Chess Playing AI with variable difficulty

Chess AI with variable difficulty level implemented using the MiniMax AB-Pruning Algorithm

Ali Imran 7 Feb 20, 2022
Official PyTorch implementation of PICCOLO: Point-Cloud Centric Omnidirectional Localization (ICCV 2021)

Official PyTorch implementation of PICCOLO: Point-Cloud Centric Omnidirectional Localization (ICCV 2021)

16 Nov 19, 2022
A Number Recognition algorithm

Paddle-VisualAttention Results_Compared SVHN Dataset Methods Steps GPU Batch Size Learning Rate Patience Decay Step Decay Rate Training Speed (FPS) Ac

1 Nov 12, 2021
Python implementation of Lightning-rod Agent, the Stack4Things board-side probe

Iotronic Lightning-rod Agent Python implementation of Lightning-rod Agent, the Stack4Things board-side probe. Free software: Apache 2.0 license Websit

2 May 19, 2022