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learn_turtle

leetcode

leetcode-1

LeetCode Top 100 Liked Questions | Top Interview Questions | LeetCode 用户最喜欢的100题 | 面试最容易被问到的题

leetcode-2

一起来刷LeetCode，一起学习，一起提高！欢迎点击 star ，欢迎在公众号「良许Linux」后台回复「leetcode」一起加入我们！

libpku

贵校课程资料民间整理

lihang_book_algorithm

致力于将李航博士《统计学习方法》一书中所有算法实现一遍

listed-company-news-crawl-and-text-analysis

从新浪财经、每经网、金融界、**证券网、证券时报网上，爬取上市公司（个股）的历史新闻文本数据进行文本分析、提取特征集，然后利用SVM、随机森林等分类器进行训练，最后对实施抓取的新闻数据进行分类预测

machinelearninginaction

Source Code for the book: Machine Learning in Action published by Manning

machinelearninginaction-1

mixup-cifar10

mixup: Beyond Empirical Risk Minimization

model-compression-deploy

model compression and deploy. compression: 1、quantization: quantization-aware-training, 16/8/4/2-bit(dorefa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、ternary/binary(twn/bnn/xnor-net); post-training-quantization, 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization folding for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape

models

Models and examples built with TensorFlow

model_compression

Implementation of model compression with knowledge distilling method.

nsga-ii

The implementation of NSGA-II with Python

nsga-ii-for-cooperative-combat

NSGA-II for cooperative model

or-tools

Google's Operations Research tools:

outlier-exposure

Deep Anomaly Detection with Outlier Exposure (ICLR 2019)

papercv

proxylessnas

[ICLR 2019] ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware.

pt.darts

PyTorch Implementation of DARTS: Differentiable Architecture Search

pumpkin-book

《机器学习》（西瓜书）公式推导解析，在线阅读地址：https://datawhalechina.github.io/pumpkin-book

pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

pygame

python

python-1

Python 入门教程：【草根学 Python （基于Python3.6）】

pytorch

pytorch-1

Tensors and Dynamic neural networks in Python with strong GPU acceleration

pytorch-classification

Classification with PyTorch.

pytorch-image-models

PyTorch image models, scripts, pretrained weights -- (SE)ResNet/ResNeXT, DPN, EfficientNet, MixNet, MobileNet-V3/V2/V1, MNASNet, Single-Path NAS, FBNet, and more

pytorch-playground

Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)