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.

Owner
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GitHub Repository
MBPO (paper: When to trust your model: Model-based policy optimization) in offline RL settings

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Neural Motion Learner With Python

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Jinseok Bae 14 Nov 28, 2022
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93 Nov 08, 2022
ManipNet: Neural Manipulation Synthesis with a Hand-Object Spatial Representation - SIGGRAPH 2021

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HE ZHANG 194 Dec 06, 2022
Styled text-to-drawing synthesis method. Featured at the 2021 NeurIPS Workshop on Machine Learning for Creativity and Design

Styled text-to-drawing synthesis method. Featured at the 2021 NeurIPS Workshop on Machine Learning for Creativity and Design

Peter Schaldenbrand 247 Dec 23, 2022
Self-Regulated Learning for Egocentric Video Activity Anticipation

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PyTorch/GPU re-implementation of the paper Masked Autoencoders Are Scalable Vision Learners

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PyTorch implementation of Federated Learning with Non-IID Data, and federated learning algorithms, including FedAvg, FedProx.

Federated Learning with Non-IID Data This is an implementation of the following paper: Yue Zhao, Meng Li, Liangzhen Lai, Naveen Suda, Damon Civin, Vik

Youngjoon Lee 48 Dec 29, 2022
Conjugated Discrete Distributions for Distributional Reinforcement Learning (C2D)

Conjugated Discrete Distributions for Distributional Reinforcement Learning (C2D) Code & Data Appendix for Conjugated Discrete Distributions for Distr

1 Jan 11, 2022
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MacroTools.jl MacroTools provides a library of tools for working with Julia code and expressions. This includes a powerful template-matching system an

FluxML 278 Dec 11, 2022
Implementation of Gans

GAN Generative Adverserial Networks are an approach to generative data modelling using Deep learning methods. I have currently implemented : DCGAN on

Sibam Parida 5 Sep 07, 2021
Recurrent Neural Network Tutorial, Part 2 - Implementing a RNN in Python and Theano

Please read the blog post that goes with this code! Jupyter Notebook Setup System Requirements: Python, pip (Optional) virtualenv To start the Jupyter

Denny Britz 863 Dec 15, 2022
This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the time series forecasting research space.

TSForecasting This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the tim

Rakshitha Godahewa 80 Dec 30, 2022
SysWhispers Shellcode Loader

Shhhloader Shhhloader is a SysWhispers Shellcode Loader that is currently a Work in Progress. It takes raw shellcode as input and compiles a C++ stub

icyguider 630 Jan 03, 2023
[CoRL 2021] A robotics benchmark for cross-embodiment imitation.

x-magical x-magical is a benchmark extension of MAGICAL specifically geared towards cross-embodiment imitation. The tasks still provide the Demo/Test

Kevin Zakka 36 Nov 26, 2022
A Python Package For System Identification Using NARMAX Models

SysIdentPy is a Python module for System Identification using NARMAX models built on top of numpy and is distributed under the 3-Clause BSD license. N

Wilson Rocha 175 Dec 25, 2022
Model of an AI powered sign language interpreter.

TEXT AND SPEECH TO SIGN LANGUAGE. A web application which takes in text or live audio speech recording as input, converts and displays the relevant Si

Mark Gatere 4 Mar 30, 2022
code for paper"A High-precision Semantic Segmentation Method Combining Adversarial Learning and Attention Mechanism"

PyTorch implementation of UAGAN(U-net Attention Generative Adversarial Networks) This repository contains the source code for the paper "A High-precis

Tong 8 Apr 25, 2022
AdamW optimizer for bfloat16 models in pytorch.

Image source AdamW optimizer for bfloat16 models in pytorch. Bfloat16 is currently an optimal tradeoff between range and relative error for deep netwo

Alex Rogozhnikov 8 Nov 20, 2022