Knowledge

Contains information links, articles, research papers, tweets, blog posts, companies etc and everything which is even minutely related to the field of Artificial Intelligence, Distributed Computing, Quantum Computing and Physics, Evolutionary Biology, Crypto-currency, Virual and Augmented Reality etc.

Educational Websites

1. Fast.ai
   1. Practical Deep Learning for Coders
   2. Cutting Edge Deep Learning for Coders
   3. Introduction to Machine Learning for Coders
   4. Computational Linear Algebra
   5. U-net
2. Deep Learning Analytics
3. Professional Conference Recordings

Learning

1. Understanding Semantic Segmentation with UNET. https://towardsdatascience.com/understanding-semantic-segmentation-with-unet-6be4f42d4b47
2. Full Stack Deep Learning
3. General Full Stack Deep Learning

Neuroscience

1. Toward an Integration of Deep Learning and Neuroscience. https://www.frontiersin.org/articles/10.3389/fncom.2016.00094/full

Datasets

1. The home of the U.S. Government’s open data. https://www.data.gov/

   Here you will find data, tools, and resources to conduct research, develop web and mobile applications, design data visualizations, and more.

2. PubMed

Repositories

1. Attention Gated Networks (Attention U-net). https://github.com/ozan-oktay/Attention-Gated-Networks
2. Yog AI. https://github.com/smellslikeml/YogAI
3. ML from Scratch. https://github.com/eriklindernoren/ML-From-Scratch
4. PyTorch GAN. https://github.com/eriklindernoren/PyTorch-GAN
5. Awesome Machine Learning.https://github.com/josephmisiti/awesome-machine-learning
   

Blogs

1. Lyrn.ai. https://www.lyrn.ai/
2. Morten Dahl.https://mortendahl.github.io/

News

Researchers

Papers

1. U-Net: Convolutional Networks for Biomedical Image Segmentation. https://arxiv.org/pdf/1505.04597.pdf
2. Fully Convolutional Networks for Semantic Segmentation. https://arxiv.org/pdf/1411.4038.pdf
3. A Novel Focal Tversky loss function with improved Attention U-Net for lesion segmentation. https://paperswithcode.com/paper/a-novel-focal-tversky-loss-function-with#code
4. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. Deep Residual Learning for Image Recognition . https://arxiv.org/abs/1512.03385
5. Private Machine Learning in TensorFlow using Secure Computation. https://arxiv.org/pdf/1810.08130.pdf

https://x.com/AIatMeta/status/1848409099949773234?t=MtySYZJ8faPj2opCAVgTEQ&s=19

Key people

Companies

1. Dropout Labs.https://medium.com/dropoutlabs/introducing-dropout-labs-d1b96f638ae2