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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
Pytorch implementation of "Geometrically Adaptive Dictionary Attack on Face Recognition" (WACV 2022)

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《Fst Lerning of Temporl Action Proposl vi Dense Boundry Genertor》(AAAI 2020)

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DC540 hacking challenge 0x00005a.

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Pytorch re-implementation of Paper: SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text Recognition (CVPR 2022)

SwinTextSpotter This is the pytorch implementation of Paper: SwinTextSpotter: Scene Text Spotting via Better Synergy between Text Detection and Text R

mxin262 183 Jan 03, 2023
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This repository contains code of face emotion recognition that was developed in the RSF (Russian Science Foundation) project no. 20-71-10010 (Efficien

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Repository for the semantic WMI loss

Installation: pip install -e . Installing DL2: First clone DL2 in a separate directory and install it using the following commands: git clone https:/

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Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference"

Noisy Natural Gradient as Variational Inference PyTorch implementation of Noisy Natural Gradient as Variational Inference. Requirements Python 3 Pytor

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UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning

UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning This is the official PyTorch implementation for UniMoCo pape

dddzg 49 Jan 02, 2023
Pacman-AI - AI project designed by UC Berkeley. Designed reflex and minimax agents for the game Pacman.

Pacman AI Jussi Doherty CAP 4601 - Introduction to Artificial Intelligence - Fall 2020 Python version 3.0+ Source of this project This repo contains a

Jussi Doherty 1 Jan 03, 2022
🏎️ Accelerate training and inference of 🤗 Transformers with easy to use hardware optimization tools

Hugging Face Optimum 🤗 Optimum is an extension of 🤗 Transformers, providing a set of performance optimization tools enabling maximum efficiency to t

Hugging Face 842 Dec 30, 2022
Twins: Revisiting the Design of Spatial Attention in Vision Transformers

Twins: Revisiting the Design of Spatial Attention in Vision Transformers Very recently, a variety of vision transformer architectures for dense predic

482 Dec 18, 2022
Understanding Convolutional Neural Networks from Theoretical Perspective via Volterra Convolution

nnvolterra Run Code Compile first: make compile Run all codes: make all Test xconv: make npxconv_test MNIST dataset needs to be downloaded, converted

1 May 24, 2022
Contrastive Learning for Compact Single Image Dehazing, CVPR2021

AECR-Net Contrastive Learning for Compact Single Image Dehazing, CVPR2021. Official Pytorch based implementation. Paper arxiv Pytorch Version TODO: mo

glassy 253 Jan 01, 2023
Multi Camera Calibration

Multi Camera Calibration 'modules/camera_calibration/app/camera_calibration.cpp' is for calculating extrinsic parameter of each individual cameras. 'm

7 Dec 01, 2022
Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing

Cerberus Transformer: Joint Semantic, Affordance and Attribute Parsing Paper Introduction Multi-task indoor scene understanding is widely considered a

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PyTorch implementation and pretrained models for XCiT models. See XCiT: Cross-Covariance Image Transformer

Official code Cross-Covariance Image Transformer (XCiT)

Facebook Research 605 Jan 02, 2023
Improving Object Detection by Label Assignment Distillation

Improving Object Detection by Label Assignment Distillation This is the official implementation of the WACV 2022 paper Improving Object Detection by L

Cybercore Co. Ltd 51 Dec 08, 2022