SDSC/open-pulse-hackathon-data-analysis huggingface dataset:
Repository: hassan11196/introtodeeplearning
Description: Lab Materials for MIT 6.S191: Introduction to Deep Learning
Primary language: Jupyter Notebook

[![banner](assets/banner.png)](http://introtodeeplearning.com)

This repository contains all of the code and software labs for [MIT 6.S191: Introduction to Deep Learning](http://introtodeeplearning.com)! All lecture slides and videos are available on the course website.


## Opening the labs in Google Colaboratory:

The 2020 6.S191 labs will be run in Google's Colaboratory, a Jupyter notebook environment that runs entirely in the cloud, you don't need to download anything. To run these labs, you must have a Google account.

On this Github repo, navigate to the lab folder you want to run (`lab1`, `lab2`, `lab3`) and open the appropriate python notebook (\*.ipynb). Click the "Run in Colab" link on the top of the lab. That's it!

## Running the labs
Now, to run the labs, open the Jupyter notebook on Colab. Navigate to the "Runtime" tab --> "Change runtime type". In the pop-up window, under "Runtime type" select "Python 3", and under "Hardware accelerator" select "GPU". Go through the notebooks and fill in the `#TODO` cells to get the code to compile for yourself!


### MIT Deep Learning package
You might notice that inside the labs we install the `mitdeeplearning` python package from the Python Package repository:

`pip install mitdeeplearning`

This package contains convienence functions that we use throughout the course and can be imported like any other Python package.

`>>> import mitdeeplearning as mdl`

We do this for you in each of the labs, but the package is also open source under the same license so you can also use it outside the class.

## Lecture Videos

[<img src="assets/video_play.png" width="500">](https://www.youtube.com/watch?v=njKP3FqW3Sk&list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI&index=1)

All lecture videos are available publicly online and linked above! Use and/or modification of lecture slides outside of 6.S191 must reference:

> © MIT 6.S191: Introduction to Deep Learning
>
> http://introtodeeplearning.com

## License
All code in this repository is copyright 2020 [MIT 6.S191 Introduction to Deep Learning](http://introtodeeplearning.com). All Rights Reserved.

Licensed under the MIT License. You may not use this file except in compliance with the License. Use and/or modification of this code outside of 6.S191 must reference:

> © MIT 6.S191: Introduction to Deep Learning
>
> http://introtodeeplearning.com
Repository: hassan11196/open-source-template
Description: A template for open source projects at Auth0

# Auth0 Open Source Template

This repo contains sample files to be used in Auth0 open source software repositories. These files are guidelines that can be used in an Auth0 or any open source project to ensure that the project is described properly, the contribution process is clear, and additional tools like CI, coverage monitors, and quality checkers are configured properly.

## Table of Contents

- [Getting Started](#getting-started)
- [Contribution](#contribution)
- [Thank You](#thank-you)
- [License](#license)

## Getting Started

This repo can be cloned, modified, then re-purposed for new open source projects. It can also be used piecemeal to improve existing repos.

### Copy README-sample.md to README.md

The core of open source repo quality is the `README.md` file that's displayed on the repo's homepage in Github. The `README-sample.md` included here was collaboratively created by Auth0's SDK engineering team and community engineering team based on samples of high-quality README files around the web.

Most sections within this file should be considered required, even if that section contains a link to a more relevant page. Certain sections will contain repo-specific information and should be modified as needed:

- Description (below the title)
- Badges
- Documentation
- Installation
- Getting Started
- Thank you
- License

Other sections should be used as-is with minimal changes:

- Table of Contents
- Contribution
- Support + Feedback
- Vulnerability Reporting
- What is Auth0?

### Modify templates in `.github`

The issue and PR templates contained in this repo are general guidelines for what to include. What is being asked for is entirely up to the repo maintainer but a template of some kind should be included.

### Update LICENSE

See `README-sample.md` for guidelines.

### Modify .gitignore

This file contains files that will be excluded from git. Modify as needed based on the technology being used.

### Modify/remove platform-specific files

Additional template files have been included here for the specific technology that we work with. These should be considered as guidelines and not enforced in any way.

## Contribution

We appreciate feedback and contribution to this template! Before you get started, please see the following:

- [Auth0's general contribution guidelines](GENERAL-CONTRIBUTING.md)
- [Auth0's code of conduct guidelines](CODE-OF-CONDUCT.md)

## Thank You!

A big thank you to all of our sources of inspiration!

- [First Contributions by @Roshanjossey](https://github.com/Roshanjossey/first-contributions)
- [First Timers Only](https://www.firsttimersonly.com/)
- [Sane Github Labels](https://medium.com/@dave_lunny/sane-github-labels-c5d2e6004b63)
- [Awesome README by @matiassingers](https://github.com/matiassingers/awesome-readme)

... and many more!

## License

This repo is covered under [The MIT License](LICENSE).
Repository: hassan11196/posthog.com
Description: Official docs, website and handbook.
Primary language: JavaScript

# PostHog.com - docs, website and handbook

This is the new company website / docs and handbook.

Please feel free to suggest any changes - see our contributing guide.

## Quick Start

1.  **Start developing.**

    Clone the repo then navigate into your new site’s directory and start it up.

    ```sh
    cd posthog.com/
    yarn install
    gatsby develop
    ```

1.  **Open the source code and start editing!**

    Your site is now running at `http://localhost:8000`!
    
    *Note: You'll also see a second link: `http://localhost:8000/___graphql`. This is a tool you can use to experiment with querying your data. Learn more about using this tool in the [Gatsby tutorial](https://www.gatsbyjs.org/tutorial/part-five/#introducing-graphiql).*