https://github.com/methyldragon/knowledge-hoard
Manifold disparate and esoteric concepts, easily found and concisely explained 📖🐲🔥
https://github.com/methyldragon/knowledge-hoard
computer-science computer-vision data-science engineering machine-learning math mathematics notes
Last synced: 6 months ago
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Manifold disparate and esoteric concepts, easily found and concisely explained 📖🐲🔥
- Host: GitHub
- URL: https://github.com/methyldragon/knowledge-hoard
- Owner: methylDragon
- License: bsd-3-clause
- Created: 2020-05-31T09:26:17.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2020-06-01T02:38:08.000Z (about 6 years ago)
- Last Synced: 2025-01-23T18:50:13.461Z (over 1 year ago)
- Topics: computer-science, computer-vision, data-science, engineering, machine-learning, math, mathematics, notes
- Homepage:
- Size: 1.44 MB
- Stars: 3
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# knowledge-hoard
This dragon hoards `k n o w l e d g e`.
[Image Source](https://iguanamouth.tumblr.com/post/90613272412/unusual-hoard-commission-for-fatetea-this-dragon)
---
## Description (and why I am doing this)
Hello! Welcome to my hoard of knowledge, shared freely and openly on the internet.
I was motivated to create this resource after continuously running up against walls when reading technical papers in various STEM fields.
Not being able to quickly look up a concept and get a succinct, understandable definition or listing of important implications is very troublesome. Even searching for them online might yield less than stellar explanations, or take far too long to find a satisfactory one. And once I've learnt something, without repeated practice or refreshers, concepts get forgotten or become murky again.
So I figured, why not apply [the](https://github.com/methylDragon/coding-notes) [same](https://github.com/methylDragon/ros-tutorials) [approach](https://github.com/methylDragon/python-data-tools-reference) [I've](https://github.com/methylDragon/linux-reference) [had](https://github.com/methylDragon/docker-reference) [when](https://github.com/methylDragon/moveit-tutorial) [learning](https://github.com/methylDragon/pcl-ros-tutorial) [something](https://github.com/methylDragon/ros-sensor-fusion-tutorial) [new](https://github.com/methylDragon/opencv-python-reference) with general or technical knowledge, and **write or record it down in a searcheable manner**? I will also be attempting to learn or explain these concepts ideally using something like the [Feynman technique](https://www.quora.com/What-is-the-Feynman-technique-in-detail), but this project is meant to be quite free flowing and informal.
As such, this project will be **evergreen** for as long as I keep continuously learning. Built for myself, questionably organised, but **free and open to share**. I will be curating a list of disparate and obscure topics, as well as including explanations that I find online or come up with myself to help render those topics as understandable as I can make them.
All motivated from the idea that, **I cannot say I've learnt or understood something until I can record it down and explain it to someone else**.
Again, I'll hope to do it **as informally as possible**. I believe that keeping things light and not couched in an academic context should help a lot of making the material more accessible, and aid in avoiding burnout or anxiety from not understanding.
What are you waiting for? Time to start learning!
## Contents
I will be exploring many different topics, but I might focus on a couple, such as:
- Math
- Computer Science
- Machine Learning
- Engineering
Though you might find the occasional life sciences or humanities, or even game design/creative concept floating somewhere in my notes! I have wide and varying interests, which don't exactly lend well to deep research, but definitely helps with integrating across domains.
## Using This Resource
### On Depth of Topics Covered
By nature of the concise way the concepts and topics are presented, this resource should be treated as a way to quickly get an introduction to and familiarity of the topic. This is because this is written to aid in understanding or reading jargon-heavy literature or papers, as well as provide quick intuitive refreshers for concepts.
**The hoard is not meant to be exhaustive or definitive!**
If you needs a much more in-depth treatise on a topic, you can either look at the references if they are cited, or search up the terms yourself with the (hopefully) better understanding of the topic you've gotten from this resource.
### Using It
You should be using this resource like an encyclopedia or a reference! This is not like my other tutorials out there!
Trying to read everything in one go might overwhelm you, I think it'd overwhelm me too!
Some recommended ways to use this resource are:
- Come to this resource to get an introduction to a particular topic you are interested in.
- Keep the relevant resource for a particular domain open while you are reading a paper to quickly `ctrl-F` and search up a concept or topic.
### Programs for Reading It
Even though this is hosted on GitHub, I'd recommend cloning the repository and using something like [Typora](https://typora.io/) to read and go through the notes! This will let you:
- Visualise the `LaTeX` math (since GitHub does not support dynamic generation of math expressions, and I don't exactly want to keep regenerating math expression images
- Easily search through outlines
This is because having access to an **outline** of headers will make searching for topics much easier. **You can also scroll up on the outline to search just within the outline**!
This will help prevent spurious matches with the body text and help focus your searches to keywords in the headers!!
**N.B.**: I'd have preferred to use something hosted online like [HackMD](https://hackmd.io/), but due to size and visibility constraints I decided against it.
## Things to be Grateful For
References will be mentioned in the individual topic sections under the notes. But [r/explainlikeimfive/](https://www.reddit.com/r/explainlikeimfive/) is going to be given a special mention for helping massively in the first few moments of trying to understand a topic.
## Contributing
Contributions by pull request will be entertained, but as this repository is a collection of things I have personally learnt, I will not merge them in until I've understood the concept!
(Of course, a quality contribution will allow me to quickly learn something new, which will then warrant it being merged in... So I guess what I'm saying is **feel free to contribute to the knowledge hoard**!)
Do ensure that any contributions are formatted similarly to the other items in the notes, and to also give credit where credit is due, and mention your sources.
## Disclaimer
I make no guarantees for accuracy! But I will be citing my sources, so please do feel free to explore on your own or issue corrections.
## Support my efforts!
[.png)](https://www.buymeacoffee.com/methylDragon)
[Or leave a tip! ヾ(°∇°*)](https://www.paypal.me/methylDragon)