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10x-scatac-2019

Code Repository for Satpathy Granja et al 2019

accum_optimizer_for_keras

wrapping a keras optimizer to implement gradient accumulation

atac-pipe

Analysis pipeline for ATAC-seq Data

awesome-automl-and-lightweight-models

A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.

awesome-automl-papers

A curated list of automated machine learning papers, articles, tutorials, slides and projects

bead-normalization

bead-based normalization of mass cytometry data

bio-10x

Use Seurat,monocle etc in R to analysis 10X single cell dataset

bio-alignanalysis

Bio Align Anlysis(scRNA,wes etc)

books

富贵必从勤苦得，男儿须读五车书

brain-segmentation-pytorch

U-Net implementation in PyTorch for FLAIR abnormality segmentation in brain MRI

catalyst

Cytometry dATa anALYsis Tools

cellcnn

Representation Learning for detection of phenotype-associated cell subsets

cellphonedb

class-balanced-loss-pytorch

Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"

closerlookfewshot

source code to ICLR'19, 'A Closer Look at Few-shot Classification'

cluster_singlecell_celltype

Use the method to auto classify cell type in single cell

combat-seq

Batch effect adjustment based on negative binomial regression for RNA sequencing count data

congan

Continious Generative Adversarial Network

coursera-ml-andrewng-notes

吴恩达老师的机器学习课程个人笔记

cytof_plasma_pma

data-iterator

This is a data iterator I write for my dataset,it also include data agumention

datascincejob

The job for science ,wechat

dcgan

dcgan-tensorflow

deeplab-pytorch

PyTorch implementation of DeepLab v2 on COCO-Stuff / PASCAL VOC

deeplab-pytorch-1

Deeplab for semantic segmentation tasks

deeplabv3

PyTorch implementation of DeepLabV3, trained on the Cityscapes dataset.

deeplearning

深度学习入门教程&&优秀文章&&Deep Learning Tutorial

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，近30万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.