MM029 – Best Sites about Machine Learning, Deep Learning and Artificial Intelligence
It’s always hard to find sources, here my collection of the best sites about State of Art in Machine Learning, Deep Learning and Artificial Intelligence @June 2020:
The father of all papers!
arXiv is a free distribution service and an open-access archive for 1,704,738 scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics.
Materials on this site are not peer-reviewed by arXiv.
2. ARXIV SANITY – HTTP://WWW.ARXIV-SANITY.COM/
Sometimes is hard to find something on arXiv, and to maintain our sanity this site came in our rescue!! Original Project @https://github.com/karpathy/arxiv-sanity-preserver
This project is a web interface that attempts to tame the overwhelming flood of papers on Arxiv.
It allows researchers to keep track of recent papers, search for papers, sort papers by similarity to any paper, see recent popular papers, to add papers to a personal library, and to get personalized recommendations of (new or old) Arxiv papers.
This code is currently running live at www.arxiv-sanity.com/, where it’s serving 25,000+ Arxiv papers from Machine Learning (cs.[CV|AI|CL|LG|NE]/stat.ML) over the last ~3 years.
3. PAPERS WITH(/) CODE – HTTPS://PAPERSWITHCODE.COM/
Really usefull for fast prototyping and playing around the paper, often I want the code of the paper.
In this website we can found every paper that has a code attached to it, even with the dataset.
The mission of Papers With Code is to create a free and open resource with Machine Learning papers, code and evaluation tables.
We believe this is best done together with the community and powered by automation.
We’ve already automated the linking of code to papers, and we are now working on automating the extraction of evaluation metrics from papers.
4. FAST AI DEEP LEARNING COURSE – HTTPS://COURSE.FAST.AI/
You want to learn artificial intelligence but you don’t know where to start? This is a good starting free course!
Currently at version 3.
Welcome! If you’re new to all this deep learning stuff, then don’t worry—we’ll take you through it all step by step. (And if you’re an old hand, then you may want to check out our advanced course: Deep Learning From The Foundations.) We do however assume that you’ve been coding for at least a year, and also that (if you haven’t used Python before) you’ll be putting in the extra time to learn whatever Python you need as you go. (For learning Python, we have a list of python learning resources available.)
5. DEEP AI – HTTPS://DEEPAI.ORG/
Just another useful website with a lot of papers and projects!
DeepAI was founded with the belief that a future built with artificial intelligence allows for the sustainable accommodation of all humanity at a high standard of living.
DeepAI develops the technologies to help make this future a reality, while moving towards the ultimate goal of making AGI directly accessible to the individual.
6. OPEN AI – HTTPS://OPENAI.COM/
The Elon Musk’s ai company, really good articles and code!
Discovering and enacting the path to safe artificial general intelligence.
7. ML SHOWCASE – HTTPS://ML-SHOWCASE.COM/
Highlighting awesome open source machine learning / AI projects
Highlighting awesome open source machine learning / AI projects
8. UC BERKELEY’S BEGINNERS’ ARTIFICIAL INTELLIGENCE COURSE – HTTP://AI.BERKELEY.EDU/HOME.HTML
University course about machine learning!
9. UC IRVINE MACHINE LEARNING REPOSITORY – HTTPS://ARCHIVE.ICS.UCI.EDU/ML/INDEX.PHP
The most famous machine learning dataset site!
We currently maintain 497 data sets as a service to the machine learning community. You may view all data sets through our searchable interface. For a general overview of the Repository, please visit our About page. For information about citing data sets in publications, please read our citation policy. If you wish to donate a data set, please consult our donation policy. For any other questions, feel free to contact the Repository librarians.
10. PROJECT AWESOME – GITHUB COLLECTIONS
If you are a coder, surely you know the awesome collections. It’s a bunch of links of the best tools/papers/examples founded by the users.
Project Awesome – A curated list of awesome machine learning frameworks, libraries and software (by language)
MACHINE LEARNING
- https://github.com/EthicalML/awesome-production-machine-learning
- https://github.com/jmschrei/awesome-machine-learning
- https://github.com/RatulGhosh/awesome-machine-learning
- https://project-awesome.org/josephmisiti/awesome-machine-learning
DEEP LEARNING
- https://github.com/ChristosChristofidis/awesome-deep-learning
- https://github.com/endymecy/awesome-deeplearning-resources
- https://project-awesome.org/guillaume-chevalier/awesome-deep-learning-resources
- https://github.com/terryum/awesome-deep-learning-papers
- https://awesomeopensource.com/projects/deep-learning-tutorial
- http://deeplearninggallery.com/
ARTIFICIAL INTELLIGENCE
- https://project-awesome.org/owainlewis/awesome-artificial-intelligence
- https://github.com/amusi/awesome-ai-awesomeness
- https://github.com/hades217/awesome-ai
- https://github.com/MRCIEU/awesome-ai
- https://libraries.io/github/tomzhang/awesome-artificial-intelligence
- https://heartbeat.fritz.ai/2019s-awesome-machine-learning-projects-with-visual-demos-e74d7d347c2
Do you like them? Good reading!
Stay Tuned!
Graziano
(Banner Image by Gerd Altmann from Pixabay)
