ErnestinaQiu's Stars
Machine-Learning-Tokyo/CNN-Architectures
ex4sperans/pruning_with_tensorflow
I demonstrate how to compress a neural network using pruning in tensorflow.
666DZY666/micronet
micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape
jingchenUSTC/SVDRecommenderSystem
将SVD应用于推荐系统中的评分预测问题
nndl/exercise
exercise for nndl
nndl/solutions
《神经网络与深度学习》课后习题答案-分享讨论
alvinwan/neural-backed-decision-trees
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
ageron/handson-ml
⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
fengdu78/deeplearning_ai_books
deeplearning.ai(吴恩达老师的深度学习课程笔记及资源)
hszhao/SAN
Exploring Self-attention for Image Recognition, CVPR2020.
aymericdamien/TensorFlow-Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
cassieeric/python_crawler
This repository is mainly about Python web crawler
iamhankai/ghostnet.pytorch
[CVPR2020] GhostNet: More Features from Cheap Operations
ageron/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
fchollet/deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
skriegman/reconfigurable_organisms
A scalable pipeline for designing reconfigurable organisms
gto76/python-cheatsheet
Comprehensive Python Cheatsheet
yzhao062/pyod
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques