Git Product home page Git Product logo

reading-group's Introduction

Welcome

If you're reading this from Github or your Markdown viewer:

Please follow the following steps to install the ML@B Research Vault. Then, read the section below the instructions in Obsidian.

  1. Clone this repository to a local folder
  2. Download Obsidian
  3. Open Obsidian and click the “Open” button next to “Open folder as vault” Open Instructions | 200
  4. Navigate to the folder you cloned the reading-group repository into Navigation Instructions | 400
  5. You should see the following Directed Acyclic Graph (DAG) in the Obsidian Graph Viewer DAG | 300
  6. Try filtering for parts of the DAG you're interested in
    1. Open the "Filters" drop down list to the top left of the graph viewer and click on the search bar
    2. Try filtering for the files in the base folder "Linear Algebra" using the "path:" option ![[Images/README/filterfile.png | 400]]
    3. Try adding a tag (as #<tag name>, e.g. #read) to a few articles and filter down to these articles using the "tag:" option ![[Images/README/readtags.png | 400]] ![[Images/README/filtertag.png | 400]]
    4. Try filtering for articles either in "Linear Algebra" OR tagged with #read by concatenating the relevant "file:" and "tag:" searches with the "OR" boolean operator. Equivalently, use the "AND" boolean operator to filter articles tagged #read within "Linear Algebra". ![[Images/README/filteror.png | 400]]
  7. Try grouping the DAG
    1. Open the "Groups" drop down list to the top left of the graph viewer, press “new group,” and explore the possible criteria ![[Images/README/groups.png | 200]]
    2. Try creating a group for each base folder in the reading-group repo using the "path:" option ![[Images/README/groupfile.png | 400]]
    3. Try adding a tag (as #<tag name>, e.g. #read) to a few articles and visualizing this group of articles with the "tag:" option ![[Images/README/readtags.png | 400]] ![[Images/README/grouptag.png | 400]]
    4. Try creating a group of articles either in "Linear Algebra" OR tagged with #read by concatenating the relevant "file:" and "tag:" searches with the "OR" boolean operator. Equivalently, use the "AND" boolean operator to group articles tagged #read within "Linear Algebra" ![[Images/README/groupor.png | 400]]
  8. Click the preview button in the top right corner with the Cmd (mac) or Ctrl (windows) button held (or whatever the obsidian popup says) to open a preview in a separate pane. Try adding the following the following and watch the preview update.
    1. A numbered list: "1. blah \n 2. blah" ->
      1. blah
      2. blah
    2. A bulleted list: "- blah \n - blah" ->
      • blah
      • blah
    3. In-text latex: "$a = 1$" -> $a = 1$
    4. Latex on its own line: "$$a = 1$$" -> $$a = 1$$
    5. An image, like the following one to help you find the preview pane: "![{Name} | {width}]({path})" -> "![Preview | 200](Images/README/preview.png)" -> Preview | 200
  9. If you create something you'd like to be added to the master repository, create a pull request on Github!

If you're reading this in Obsidian:

You're in the right place. Welcome to the ML@B Research vault! This is a folder of markdown files (see Markdown Guide) meant to be a central repository for ML@B research knowledge. It will be organized as an Obsidian vault, so be sure to download Obsidian if you wish to use it. This folder will be shared with all ML@B members and updated via git. It is intended to serve as

  1. A structured, piece-by-piece educational resource for ML@B members unfamiliar with many areas of ML
  2. An unstructured venue for tinkering with new ideas
  3. A tool for transforming unstructured exploration into structured, absorbable knowledge

As more is decided regarding the structure of our notes, we will add to this note explaining the organization of the vault, and giving instructions to new members about how to get involved.

Notation

  • $\mathcal{D}(v)$ refers to a distribution over the variable $v$

reading-group's People

Contributors

kiran-ganeshan avatar sohompaul avatar ashwinreddy avatar axquaris avatar

Stargazers

Aryan Jain avatar

Watchers

 avatar  avatar Viraat Chandra avatar

Forkers

kgshai

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.