Build your neural network easy and fast, 莫烦Python中文教学
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Updated
Mar 23, 2023 - Jupyter Notebook
Build your neural network easy and fast, 莫烦Python中文教学
Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学
Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.
Educational deep learning library in plain Numpy.
🔬 Nano size Theano LSTM module
Artificial Intelligence Learning Notes.
Complementary code for the Targeted Dropout paper
MNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented.
repo that holds code for improving on dropout using Stochastic Delta Rule
Complex-valued neural networks for pytorch and Variational Dropout for real and complex layers.
[TPAMI 2022] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang
A Deep Learning and preprocessing framework in Rust with support for CPU and GPU.
Single (i) Cell R package (iCellR) is an interactive R package to work with high-throughput single cell sequencing technologies (i.e scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq and Spatial Transcriptomics (ST)).
My workshop on machine learning using python language to implement different algorithms
PyTorch Implementations of Dropout Variants
Bayesian Neural Network in PyTorch
Implementation of DropBlock in Pytorch
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