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A paper list of object detection using deep learning.
深度学习相关的模型训练、评估和预测相关代码
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
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,50余万字。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
A collection of various deep learning architectures, models, and tips
深度学习入门的一些简单例子
A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors which can be used for ANN search.
Deep Matching, Correlation and Prediction (DeepMCP) Model
Deep Reinforcement Learning Lab, a platform designed to make DRL technology and fun for everyone
DREN:Deep Rotation Equivirant Network
Code for the IJCAI'19 paper "Deep Session Interest Network for Click-Through Rate Prediction"
Deep Spatio-Temporal Neural Network (DSTN)
Code for paper "Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning"
EasyTransfer is designed to make the development of transfer learning in NLP applications easier.
code of our AAAI 2021 paper Capturing Delayed Feedback in Conversion Rate Prediction via Elapsed-Time Sampling
A distributed graph deep learning framework.
An reimplement of faster r-cnn(resnet) with pytorch
FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation.
Library for fast text representation and classification.
手把手撕LeetCode题目,扒各种算法套路的裤子。English version supported! Crack LeetCode, not only how, but also why.
Graph Attention Networks (https://arxiv.org/abs/1710.10903)
Implementation of Graph Convolutional Networks in TensorFlow
This is a PyTorch implementation of the GeniePath model in <GeniePath: Graph Neural Networks with Adaptive Receptive Paths> (https://arxiv.org/abs/1802.00910)
GNN综述阅读报告
Implementation and experiments of graph embedding algorithms.deep walk,LINE(Large-scale Information Network Embedding),node2vec,SDNE(Structural Deep Network Embedding),struc2vec
Representation learning on large graphs using stochastic graph convolutions.
ICME2019&字节跳动 短视频内容理解与推荐竞赛rank14方案
Fit interpretable models. Explain blackbox machine learning.
关于Python的面试题
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.