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18.06-linalg-notes

MIT-18.06-线性代数-完整笔记

alexnet

Implement AlexNet with TensorFlow on MNIST

awesome-face_recognition

papers about Face Detection; Face Alignment; Face Recognition && Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution && Face Deblurring; Face Generation && Face Synthesis; Face Transfer; Face Anti-Spoofing; Face Retrieval;

awesome-federated-machine-learning

A curated list of awesome federated machine learning resources, including research papers, codes, tutorials, blogs and beyond

awesome-mac

 Now we have become very big, Different from the original idea. Collect premium software in various categories.

baiduyun

🖖油猴脚本 一个脚本搞定百度网盘下载

bam

Implementation of BAM: Bottleneck Attention Module with TensorFLow

blockchain

区块链 - 中文资源

c-plus-plus-learning

cbam

Implement CBAM：Convolutional Block Attention Module with TensorFlow

center_loss_with_mnist

chinese_history

Complete set of Chinese History E-books. :books: 完整全套的**历史电子版

clean-picture

cnn-architecture-summary

Simple Summary of CNN Architecture

codewards

Codewards刷题记录

compare_gan

Compare GAN code.

conv_arithmetic

A technical report on convolution arithmetic in the context of deep learning

convert_fer2013_to_image

convert_mnist_to_images

将mnist二进制形式解析成图片格式

d2l-zh

《动手学深度学习》，英文版即伯克利深度学习（STAT 157，2019春）教材。面向中文读者、能运行、可讨论。

daily-paper-computer-vision

记录每天整理的计算机视觉/深度学习/机器学习相关方向的论文

dcgan-tensorflow

TensorFlow implementation of DCGAN

deblurgan

Implement DeblurGAN with TensorFlow

deblurgan-tf

deep-learning-in-production

In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

deep3dfacereconstruction

Deep3DFaceReconstruction

deep_learning_object_detection

A paper list of object detection using deep learning.

deepid

tensorflow + python3实现，目标是实现DeepID2+

deeplearning

Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现

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