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22 lines
1.2 KiB
Markdown
22 lines
1.2 KiB
Markdown
# Ressources
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## Simple Neural Network
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- [3Blue1Brown](https://www.3blue1brown.com/topics/neural-networks)
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- [Medium](https://medium.com/@14prakash/back-propagation-is-very-simple-who-made-it-complicated-97b794c97e5c)
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- [Simeon Kostadinov: Understanding Backpropagation](https://towardsdatascience.com/understanding-backpropagation-algorithm-7bb3aa2f95fd)
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- [Tobias Hill: Gradient Descent](https://towardsdatascience.com/part-2-gradient-descent-and-backpropagation-bf90932c066a)
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- [Adam Optimizer](https://arxiv.org/pdf/1412.6980.pdf)
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## Convolutional Neural Network
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- [The Independent Code](https://www.youtube.com/watch?v=Lakz2MoHy6o)
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## Jeux de données
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- [MNIST](http://yann.lecun.com/exdb/mnist/)
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- [ImageNet](https://www.image-net.org/index.php)
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## CUDA
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- [Introduction à CUDA](https://developer.nvidia.com/blog/even-easier-introduction-cuda/) (Documentation Nvidia)
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- [Gestion des erreurs](https://developer.nvidia.com/blog/how-query-device-properties-and-handle-errors-cuda-cc/) (Documentation Nvidia)
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- [Unified Memory](https://on-demand.gputechconf.com/gtc/2017/presentation/s7285-nikolay-sakharnykh-unified-memory-on-pascal-and-volta.pdf) (Présentation Nvidia)
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