GenericNeuralNetwork
papers-I-read
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1 | 942 | |
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3.2 | 0.0 | |
about 3 years ago | about 1 year ago | |
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GenericNeuralNetwork
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Tracking mentions began in Dec 2020.
papers-I-read
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👨‍🎓️📊 Data Scientist— 12 Steps From Beginner to Pro
It is simply impossible to keep track of all publications. The Reddit branches listed above will help to isolate the most important texts (since the author became the head of the AI ​​department at Tesla, the site began to break more often, but it’s still the best tool). There is also such a list of articles with comments and recordings of webinars from the YouTube channel Kaggle with parsing of scientific articles related to data science algorithms.
What are some alternatives?
dnn_from_scratch - A high level deep learning library for Convolutional Neural Networks,GANs and more, made from scratch(numpy/cupy implementation).
REPL - The Learning Hub for UoL's Online CS Students
Spiking-Neural-Network-SNN-with-PyTorch-where-Backpropagation-engenders-STDP - What about coding a Spiking Neural Network using an automatic differentiation framework? In SNNs, there is a time axis and the neural network sees data throughout time, and activation functions are instead spikes that are raised past a certain pre-activation threshold. Pre-activation values constantly fades if neurons aren't excited enough.
lela - Lela is a smart dietician who can help you to maintain diet and it also has Yoga posture detection feature where users can practice yoga at their home. https://lela-dietician.herokuapp.com
UBB-INFO - All projects from university.
awesome-public-datasets - A topic-centric list of HQ open datasets. [Moved to: https://github.com/awesomedata/awesome-public-datasets]
Awesome-Diffusion-Models - A collection of resources and papers on Diffusion Models