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algorithms icon algorithms

The codes and my solutions to exercises from the book "Algorithms" (4th edition) by Robert Sedgewick and Kevin Wayne.

algorithms-1 icon algorithms-1

AlgorithmsTest is Code from the book "Algorithms" (4th ed.) by Robert Sedgewick and Kevin Wayne,算法第四版书中代码以及后面的习题,AlgorithmsExercise是一些牛客网上的题目,AlgorithmsReplenish是一些算法的补充

clue icon clue

中文任务基准测评 Chinese Language Understanding Evaluation Benchmark: datasets, baselines, pre-trained models, corpus and leaderboard

cnn-lstm-bilstm-deepcnn-clstm-in-pytorch icon cnn-lstm-bilstm-deepcnn-clstm-in-pytorch

In pytorch Learing Neural Networks likes CNN(Convolutional Neural Networks for Sentence Classification (Y.Kim, EMNLP 2014) 、LSTM、BiLSTM、DeepCNN 、CLSTM、CNN and LSTM

crawlab icon crawlab

Celery-based web crawler admin platform for managing distributed web spiders regardless of languages and frameworks.

deeplearning-500-questions icon 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,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

doubanrecommend icon doubanrecommend

基于豆瓣图书的推荐、知识图谱与知识引擎简单构建neo4j

fucking-algorithm icon fucking-algorithm

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.

ijcai-bai2014-2019 icon ijcai-bai2014-2019

整理IJCAI2014到2019年生物信息(集中在药物)方面的机器学习方法

kashgari icon kashgari

Kashgari is a Production-ready NLP Transfer learning framework for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.

mxnet icon mxnet

efficient, flexible, distributed deep learning framework

nlp-tutorial icon nlp-tutorial

Natural Language Processing Tutorial for Deep Learning Researchers

node-vue-moba icon node-vue-moba

Node.js (Express.js) + Vue.js (Element UI) 全栈开发王者荣耀手机端官网和管理后台

nutui-demo icon nutui-demo

nutui demo (vite 、vue/cli、cdn、ts)多种模式使用示例

paws icon paws

This dataset contains 108,463 human-labeled and 656k noisily labeled pairs that feature the importance of modeling structure, context, and word order information for the problem of paraphrase identification.

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