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

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Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.

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.

Complex-valued neural networks for pytorch and Variational Dropout for real and complex layers.

repo that holds code for improving on dropout using Stochastic Delta Rule

PyTorch implementations of LSTM Variants (Dropout + Layer Norm)

A Deep Learning and preprocessing framework in Rust with support for CPU and GPU.

datagrand 2019 information extraction competition rank9

iCellR is an interactive R package designed to facilitate the analysis and visualization of high-throughput single-cell sequencing data. It supports a variety of single-cell technologies, including scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq, and Spatial Transcriptomics (ST).

[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

My workshop on machine learning using python language to implement different algorithms

Bayesian Neural Network in PyTorch

PyTorch Implementations of Dropout Variants

Implementation of DropBlock in Pytorch