Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/mmlouamri/awesome

This repository is a collection of interesting technical resources that I have found on the internet.
https://github.com/mmlouamri/awesome

List: awesome

Last synced: about 1 month ago
JSON representation

This repository is a collection of interesting technical resources that I have found on the internet.

Host: GitHub
URL: https://github.com/mmlouamri/awesome
Owner: mmlouamri
Created: 2023-03-14T19:20:25.000Z (over 1 year ago)
Default Branch: main
Last Pushed: 2023-03-19T09:18:48.000Z (over 1 year ago)
Last Synced: 2024-04-10T15:57:35.611Z (5 months ago)
Size: 14.6 KB
Stars: 0
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md

Awesome Lists containing this project

ultimate-awesome - awesome - This repository is a collection of interesting technical resources that I have found on the internet. (Other Lists / PowerShell Lists)

README

        # AWESOME

This repository is a collection of interesting technical resources that I have found on the internet. The resources are categorized and listed in the `README.md` file for easy reference.

> If you have come across any interesting technical resources that you think would be a great addition to this repository, please don't hesitate to share them with me 🙏! Whether it's a helpful blog post, an informative video, or a useful library or tool.

## Content

- [Academia](#academia)

- [Artificial Intelligence](#artificial-intelligence)

- [Computer Science](#computer-science)

- [Mathematics](#mathematics)

- [Quantum](#quantum)

- [Physics](#physics)

- [Web Dev](#web)

## Academia

- [A Survival Guide to a PhD](https://karpathy.github.io/2016/09/07/phd/)

## Artificial Intelligence

- [Deep Learning with PyTorch: A 60min Blitz](https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html)

- [The Neural Network Zoo](https://www.asimovinstitute.org/neural-network-zoo/)

- [#258 | Yann LeCun: Dark Matter of Intelligence and Self-Supervised Learning | Lex Fridman Podcast](https://open.spotify.com/episode/6NJt7waroZKSbkt9sZlD7I)

- [MIT 6.S191 - Introduction to Deep Learning](http://introtodeeplearning.com/)

- [Why Neural Networks can learn (almost) anything](https://www.youtube.com/watch?v=0QczhVg5HaI)

- [Deep Learning Basics: Introduction and Overview by Lex Fridman](https://www.youtube.com/watch?v=O5xeyoRL95U)

- [Comment ces IA inventent-elles des images ? (Stable Diffusion, Midjourney, and DALL-E)](https://www.youtube.com/watch?v=tdelUss-5hY)

  - [Supervised Learning](https://youtu.be/tdelUss-5hY?t=140)

  - [Generative Adversial Nets (GANs)](https://youtu.be/tdelUss-5hY?t=450)

  - [Supervised vs Unsupervised learning](https://youtu.be/tdelUss-5hY?t=644)

  - [Diffusion models](https://youtu.be/tdelUss-5hY?t=920)

- [Comment les I.A. font-elles pour comprendre notre langue ?](https://www.youtube.com/watch?v=CsQNF9s78Nc)

  - [Supervised Learning](https://youtu.be/CsQNF9s78Nc?t=70)

  - [Convolutional Neural Networks (CNN)](https://youtu.be/CsQNF9s78Nc?t=200)

  - [Natural Language Processing](https://youtu.be/CsQNF9s78Nc?t=415)

  - [Word Embedding](https://youtu.be/CsQNF9s78Nc?t=554)

  - [Recurrent Neural Networks (RNN)](https://youtu.be/CsQNF9s78Nc?t=885)

    - [Classification (e.g: Sentiment Analysis)](https://youtu.be/CsQNF9s78Nc?t=1080)

    - [Translation](https://youtu.be/CsQNF9s78Nc?t=1130)

    - [Memory issue (LSTM, GRU, Attention, Transformers)](https://youtu.be/CsQNF9s78Nc?t=1275)

## Computer Science

- [15 Sorting Algorithms in 6 Minutes](https://www.youtube.com/watch?v=kPRA0W1kECg)

- [8 Design Patterns EVERY Developer Should Know](https://www.youtube.com/watch?v=tAuRQs_d9F8)

  - [Factory](https://youtu.be/tAuRQs_d9F8?t=45)

  - [Builder](https://youtu.be/tAuRQs_d9F8?t=95)

  - [Singleton](https://youtu.be/tAuRQs_d9F8?t=143)

  - [Observer](https://youtu.be/tAuRQs_d9F8?t=218)

  - [Iterator](https://youtu.be/tAuRQs_d9F8?t=312)

  - [Strategy](https://youtu.be/tAuRQs_d9F8?t=388)

  - [Adapter](https://youtu.be/tAuRQs_d9F8?t=438)

  - [Facade](https://youtu.be/tAuRQs_d9F8?t=502)

## Mathematics

## Quantum

- [Introduction to Quantum Computing : William Oliver - MIT](https://www.youtube.com/watch?v=lK6fC8E1XPE)

  - [Computing Development Timeline](https://youtu.be/lK6fC8E1XPE?t=170)

  - [How is a Quantum Computer Different?](https://youtu.be/lK6fC8E1XPE?t=400)

  - [Quantum Algorithm](https://youtu.be/lK6fC8E1XPE?t=920)

  - [Superconducting qubit](https://youtu.be/lK6fC8E1XPE?t=1445) 

  - [Quantum Errror Correction analogy with Lacrosse](https://youtu.be/lK6fC8E1XPE?t=2045)

 

- [The Story of Shor's Algorithm, Straight From the Source | Peter Shor](https://www.youtube.com/watch?v=6qD9XElTpCE)

  - [Simon's, discrete log, and factoring problems](https://youtu.be/6qD9XElTpCE?t=480)

  - [Error correction](https://youtu.be/6qD9XElTpCE?t=1115)

  - [Quantum error correction](https://youtu.be/6qD9XElTpCE?t=1345)

## Physics

- [Les inégalités de BELL & les expériences d'Alain ASPECT](https://www.youtube.com/watch?v=28UN70790Do)

- [Intro to Special Relativity Course](https://www.youtube.com/playlist?list=PLoaVOjvkzQtyjhV55wZcdicAz5KexgKvm)

## Web

- [What the heck is the event loop anyway? | Philip Roberts | JSConf EU](https://www.youtube.com/watch?v=8aGhZQkoFbQ)