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

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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.

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GitHub Repository
Revisting Open World Object Detection

Revisting Open World Object Detection Installation See INSTALL.md. Dataset Our new data division is based on COCO2017. We divide the training set into

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Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association" in PyTorch.

openpifpaf Continuously tested on Linux, MacOS and Windows: New 2021 paper: OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Te

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Animation of solving the traveling salesman problem to optimality using mixed-integer programming and iteratively eliminating sub tours

tsp-streamlit Animation of solving the traveling salesman problem to optimality using mixed-integer programming and iteratively eliminating sub tours.

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Code used for the results in the paper "ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning"

Code used for the results in the paper "ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning" Getting started Prerequisites CUD

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Code for the paper 'A High Performance CRF Model for Clothes Parsing'.

Clothes Parsing Overview This code provides an implementation of the research paper: A High Performance CRF Model for Clothes Parsing Edgar Simo-S

Edgar Simo-Serra 119 Nov 21, 2022
Byzantine-robust decentralized learning via self-centered clipping

Byzantine-robust decentralized learning via self-centered clipping In this paper, we study the challenging task of Byzantine-robust decentralized trai

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Fully Convlutional Neural Networks for state-of-the-art time series classification

Deep Learning for Time Series Classification As the simplest type of time series data, univariate time series provides a reasonably good starting poin

Stephen 572 Dec 23, 2022
Python framework for Stochastic Differential Equations modeling

SDElearn: a Python package for SDE modeling This package implements functionalities for working with Stochastic Differential Equations models (SDEs fo

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Open source repository for the code accompanying the paper 'PatchNets: Patch-Based Generalizable Deep Implicit 3D Shape Representations'.

PatchNets This is the official repository for the project "PatchNets: Patch-Based Generalizable Deep Implicit 3D Shape Representations". For details,

16 May 22, 2022
Minimal implementation of Denoised Smoothing: A Provable Defense for Pretrained Classifiers in TensorFlow.

Denoised-Smoothing-TF Minimal implementation of Denoised Smoothing: A Provable Defense for Pretrained Classifiers in TensorFlow. Denoised Smoothing is

Sayak Paul 19 Dec 11, 2022
"Neural Turing Machine" in Tensorflow

Neural Turing Machine in Tensorflow Tensorflow implementation of Neural Turing Machine. This implementation uses an LSTM controller. NTM models with m

Taehoon Kim 1k Dec 06, 2022
Pytorch Implementation of PointNet and PointNet++++

Pytorch Implementation of PointNet and PointNet++ This repo is implementation for PointNet and PointNet++ in pytorch. Update 2021/03/27: (1) Release p

Luigi Ariano 1 Nov 11, 2021
NHS AI Lab Skunkworks project: Long Stayer Risk Stratification

NHS AI Lab Skunkworks project: Long Stayer Risk Stratification A pilot project for the NHS AI Lab Skunkworks team, Long Stayer Risk Stratification use

NHSX 21 Nov 14, 2022
Western-3DSlicer-Modules - Point-Set Registrations for Ultrasound Probe Calibrations

Point-Set Registrations for Ultrasound Probe Calibrations -Undergraduate Thesis-

Matteo Tanzi 0 May 04, 2022
Code for paper Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting

Decoupled Spatial-Temporal Graph Neural Networks Code for our paper: Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting.

S22 43 Jan 04, 2023
Activating More Pixels in Image Super-Resolution Transformer

HAT [Paper Link] Activating More Pixels in Image Super-Resolution Transformer Xiangyu Chen, Xintao Wang, Jiantao Zhou and Chao Dong BibTeX @article{ch

XyChen 270 Dec 27, 2022
BERTMap: A BERT-Based Ontology Alignment System

BERTMap: A BERT-based Ontology Alignment System Important Notices The relevant paper was accepted in AAAI-2022. Arxiv version is available at: https:/

KRR 36 Dec 24, 2022
Official repository of "DeepMIH: Deep Invertible Network for Multiple Image Hiding", TPAMI 2022.

DeepMIH: Deep Invertible Network for Multiple Image Hiding (TPAMI 2022) This repo is the official code for DeepMIH: Deep Invertible Network for Multip

Junpeng Jing 67 Nov 22, 2022
Polynomial-time Meta-Interpretive Learning

Louise - polynomial-time Program Learning Getting help with Louise Louise's author can be reached by email at Stassa Patsantzis 64 Dec 26, 2022

This is the official PyTorch implementation for "Mesa: A Memory-saving Training Framework for Transformers".

Mesa: A Memory-saving Training Framework for Transformers This is the official PyTorch implementation for Mesa: A Memory-saving Training Framework for

Zhuang AI Group 105 Dec 06, 2022