seeker1943 Goto Github PK

learnopencv

Learn OpenCV : C++ and Python Examples

leetcode

:pencil: Python / C++ 11 Solutions of All LeetCode Questions

leetcode-1

:pencil2: LeetCode solutions in C++ 11 and Python3

leetcodetop

汇总各大互联网公司容易考察的高频leetcode题🔥

leveldb

推荐一个学习C++的方法，适合有一定基础的同学。先读effective c++，一天能搞定（从c转读第二版，从java等转读第三版），然后读google c++ style。再是看leveldb代码（http://t.cn/aYyqjo 多谢@apc2 推荐），Sanjay和Jeff所写，简短完备，非常优美，完美阐述前两者所列的原则。

lianjia-scrawler

链家二手房租房在线数据，存量房交易服务平台数据，详细数据分析教程

librealsense-patch

modify patch-realsense-ubuntu-xenial.sh in order to support the new ubuntu kernel(4.8.0-xx-generic)

librecommender

Versatile End-to-End Recommender System (TensorFlow Based)

lic2019-competition

2019语言与智能技术竞赛-基于知识图谱的主动聊天

lic2019-dureader2.0-rank2

Rank2 solution (no-BERT) for 2019 Language and Intelligence Challenge - DuReader2.0 Machine Reading Comprehension.

license-plate-detect-recognition-via-deep-neural-networks-accuracy-up-to-99.9

works in real-time with detection and recognition accuracy up to 99.8% for Chinese license plates: 100 ms/plate

lifelines

Survival analysis in Python

lintcode

:pencil2: C++ 11 Solutions of All 289 LintCode Problems

linux_ipc

关于linux ipc进程间通信自己的收录的一些代码

list_of_recommender_systems

A List of Recommender Systems and Resources

lsd_slam

LSD-SLAM

machine-learning

关于机器学习的内容

machine-learning-interview

Machine Learning Interviews from FAAG, Snapchat, LinkedIn.

machine-learning-learning-notes

周志华《机器学习》又称西瓜书是一本较为全面的书籍，书中详细介绍了机器学习领域不同类型的算法(例如：监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等)，记录了本人在学习过程中的理解思路与扩展知识点，希望对新人阅读西瓜书有所帮助！

machinelearning

Machine Learning in Action（机器学习实战）

macropodus

Macropodus：自然语言处理工具，基于Albert+BiLSTM+CRF深度学习网络架构，中文分词，命名实体识别，新词发现，关键词，文本摘要，文本相似度，科学计算器，中文数字阿拉伯数字(罗马数字)转换。tookit of NLP，CWS(chinese word segnment)，NER(name entity recognition)，Find(new words discovery)，Keyword(keyword extraction)，Summarize(text summarization)，Sim(text similarity)，Calculate(scientific calculator)，Chi2num(chinese number to arabic number)

makeup

让你的“女神”逆袭，代码撸彩妆（画妆）

map

mean Average Precision - This code evaluates the performance of your neural net for object recognition.

mdenas

Multinomial Distribution Learning for Effective Neural Architecture Search

mechanicalsoup

A Python library for automating interaction with websites.

medical-image-registration

a project for developing registration tools with convolutional neural networks

metann-book

《C++模板元编程实战：一个深度学习框架的初步实现》

metapruning

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

microservices

Microservices from Design to Deployment 中文版 《微服务：从设计到部署》