{"id":119805,"url":"https://github.com/BinbinBian/Awesome-Code","name":"Awesome-Code","description":"Links to a curated list of awesome implementations of  models.","projects_count":64,"last_synced_at":"2026-04-14T06:00:38.202Z","repository":{"id":96779385,"uuid":"61931741","full_name":"BinbinBian/Awesome-Code","owner":"BinbinBian","description":"Links to a curated list of awesome implementations of  models.","archived":false,"fork":false,"pushed_at":"2017-04-17T07:11:42.000Z","size":19,"stargazers_count":135,"open_issues_count":1,"forks_count":60,"subscribers_count":18,"default_branch":"master","last_synced_at":"2026-03-02T16:46:32.140Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/BinbinBian.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2016-06-25T07:18:31.000Z","updated_at":"2025-01-25T23:54:26.000Z","dependencies_parsed_at":null,"dependency_job_id":"eb27b3ed-4f5a-4c5c-a52d-6fd9ccf80ef8","html_url":"https://github.com/BinbinBian/Awesome-Code","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/BinbinBian/Awesome-Code","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BinbinBian%2FAwesome-Code","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BinbinBian%2FAwesome-Code/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BinbinBian%2FAwesome-Code/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BinbinBian%2FAwesome-Code/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/BinbinBian","download_url":"https://codeload.github.com/BinbinBian/Awesome-Code/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BinbinBian%2FAwesome-Code/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30571148,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-16T06:02:37.763Z","status":"ssl_error","status_checked_at":"2026-03-16T06:02:14.913Z","response_time":96,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"readme":"# Awesome-Code\n- Links to a curated list of awesome implementations of neural network models.（tensorflow,torch,theano,keras,...）\n- Mainly Question Answering,Machine comprehension,Sentiment Analysis...\n- Contributions are welcomed.\n\n##Table of Contents\n- [Python](#python)\n- [Tensorflow](#tensorflow)\n- [Theano](#theano)\n- [Keras](#keras)\n- [Torch](#torch)\n- [Matlab](#matlab)\n- [Deep Reinforcement Learning](#Deep Reinforcement Learning)\n\n\u003ca name=\"python\" /\u003e\n##Python\n- [context2vec: Learning Generic Context Embedding with Bidirectional LSTM](https://github.com/orenmel/context2vec)\n- [Deep Unordered Composition Rivals Syntactic Methods for Text Classification(Deep Averaging Networks ACL2015)](https://github.com/miyyer/dan)\n\n\n\u003ca name=\"tensorflow\" /\u003e\n##Tensorflow\n- [Neural Turing Machine(NMT)](https://github.com/carpedm20/NTM-tensorflow).Taehoon Kim’s(Tensorflow)\n- [Neural Turing Machine(NMT)](https://github.com/kaishengtai/torch-ntm). Kai Sheng Tai’s (Torch)\n- [Neural Turing Machine(NMT)](https://github.com/shawntan/neural-turing-machines)Shawn Tan’s (Thenao)\n- [Neural Turing Machine(NMT)](https://github.com/fumin/ntm)Fumin’s (Go)\n- [Neural Turing Machine(NMT)](https://github.com/snipsco/ntm-lasagne)Snip’s (Lasagne)\n- [Neural GPUs Learn Algorithms](https://github.com/tensorflow/models/tree/master/neural_gpu)\n- [A Neural Attention Model for Abstractive Summarization](https://github.com/BinbinBian/neural-summary-tensorflow)\n- [Recurrent Convolutional Memory Network](https://github.com/carpedm20/RCMN)\n- [End-To-End Memory Network](https://github.com/carpedm20/MemN2N-tensorflow)@carpedm20\n- [End-To-End Memory Network](https://github.com/domluna/memn2n)@domluna\n- [Neural Variational Inference for Text Processing](https://github.com/carpedm20/variational-text-tensorflow)---[wikiQA Corpus]()\n- [Word2Vec](https://github.com/carpedm20/word2vec-tensorflow)\n- [CNN code for insurance QA(question Answer matching)](https://github.com/BinbinBian/insuranceQA-cnn)---[InsuranceQA Corpus](https://github.com/shuzi/insuranceQA)\n- [Some experiments on MovieQA with Hsieh,Tom and Huang in AMLDS](https://github.com/YCKung/MovieQA)\n- [Teaching Machines to Read and Comprehend](https://github.com/carpedm20/attentive-reader-tensorflow)\n- [Convolutional Neural Networks for Sentence Classification (kIM.EMNLP2014)](https://github.com/dennybritz/cnn-text-classification-tf)Tensorflow\n- [Convolutional Neural Networks for Sentence Classification (kIM.EMNLP2014)](https://github.com/yoonkim/CNN_sentence)Theano\n- [Separating Answers from Queries for Neural Reading Comprehension](https://github.com/dirkweissenborn/qa_network)\n- [Neural Associative Memory for Dual-Sequence Modeling](https://github.com/dirkweissenborn/dual_am_rnn)\n- [The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems.](https://github.com/dennybritz/chatbot-retrieval)\n- [Key-Value Memory Networks for Directly Reading Documents](https://github.com/siyuanzhao/key-value-memory-networks)\n- [A statistical natural language generator for spoken dialogue systems(SIGDIAL 2016 short paper)](https://github.com/UFAL-DSG/tgen)\n\n\u003ca name=\"theano\" /\u003e\n##Theano\n- [ End-To-End Memory Networks, formerly known as Weakly Supervised Memory Networks](https://github.com/npow/MemN2N)\n- [Memory Networks](https://github.com/npow/MemNN)\n- [Dynamic Memory Networks](https://github.com/swstarlab/DynamicMemoryNetworks)\n- [Ask Me Anything: Dynamic Memory Networks for Natural Language Processing](https://github.com/YerevaNN/Dynamic-memory-networks-in-Theano)YerevaNN’s (Theano)\n- [Memory Networks](https://github.com/facebook/MemNN)Facebook’s (Torch/Matlab)\n- [Recurrent Neural Networks with External Memory for Language Understanding](https://github.com/npow/RNN-EM)\n- [Attention Sum Reader model as presented in \"Text Comprehension with the Attention Sum Reader Network\"](https://github.com/rkadlec/asreader)---[ CNN and Daily Mail news data QA]()\n- [character-level language models](https://github.com/lipiji/rnn-theano)\n- [Hierarchical Encoder-Decoder](https://github.com/BinbinBian/hierarchical-encoder-decoder)\n- [A Recurrent Latent Variable Model for Sequential Data](https://github.com/jych/nips2015_vrnn)\n- [A Fast Unified Model for Sentence Parsing and Understanding(Stack-augmented Parser-Interpreter Neural Network)](https://github.com/stanfordnlp/spinn)\n- [ Semi-supervised Question Retrieval with Gated Convolutions. NAACL 2016](https://github.com/taolei87/rcnn)\n- [ Molding CNNs for text: non-linear, non-consecutive convolutions. EMNLP 2015](https://github.com/taolei87/rcnn)\n- [Tree RNNs](https://github.com/ofirnachum/tree_rnn)\n- [A Character-Level Decoder without Explicit Segmentation for Neural Machine Translation(ACL2016)](https://github.com/nyu-dl/dl4mt-cdec)\n- [Charagram: Embedding Words and Sentences via Character n-grams](https://github.com/jwieting/charagram)\n- [Towards Universal Paraphrastic Sentence Embeddings](https://github.com/jwieting/iclr2016)\n- [Dependency-based Convolutional Neural Networks for Sentence Embedding](https://github.com/cosmmb/DCNN)\n- [Siamese-LSTM - Siamese Recurrent Neural network with LSTM for evaluating semantic similarity between sentences.（AAAI2016））](https://github.com/aditya1503/Siamese-LSTM)\n\n\u003ca name=\"keras\"/\u003e\n##Keras\n- [Learning text representation using recurrent convolutional neural network with highway layers](https://github.com/wenying45/deep_learning_tutorial/tree/master/rcnn-hw)\n\n\u003ca name=\"torch\"/\u003e\n##Torch\n- [Sequence-to-sequence model with LSTM encoder/decoders and attention](https://github.com/harvardnlp/seq2seq-attn)\n- [Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks](https://github.com/rajarshd/ChainsOfReasoning/tree/master/model)\n- [Recurrent Memory Network for Language Modeling](https://github.com/ketranm/RMN)\n- [Bag of Tricks for Efficient Text Classification.(FastText)](https://github.com/kemaswill/fasttext_torch)\n- [Bag of Tricks for Efficient Text Classification.(FastText)](https://github.com/facebookresearch/fastText)Facebook C++\n- [Character-Aware Neural Language Models (AAAI 2016).](https://github.com/yoonkim/lstm-char-cnn)\n- [Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks(Tree-LSTM)](https://github.com/stanfordnlp/treelstm)\n- [A Neural Attention Model for Abstractive Summarization.](https://github.com/facebook/NAMAS)\n- [Text Understanding with the Attention Sum Reader Network, Kadlec et al., ACL 2016.](https://github.com/ganeshjawahar/torch-teacher)\n- [A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task, Chen et al., ACL 2016.](https://github.com/ganeshjawahar/torch-teacher)\n- [The Goldilocks Principle: Reading Children's Books with Explicit Memory Representations, Hill et al., ICLR 2016.](https://github.com/ganeshjawahar/torch-teacher)\n\n\u003ca name=\"matlab\"\u003e\n##Matlab\n- [When Are Tree Structures Necessary for Deep Learning of Representations](https://github.com/jiweil/Sequence-Models-on-Stanford-Treebank)\n \n \n\u003cA name=\"Deep Reinforcement Learning\"\u003e\n##Deep Reinforcement Learning\n\n\n##===========================================\n\u003cA name=\"mldptt\"\u003e\n##machine learning and deep learning tutorials, articles and other resources\n- [machine learning and deep learning tutorials, articles and other resources](https://github.com/ujjwalkarn/Machine-Learning-Tutorials)\n- [Knowledge Graph Embeddings including TransE, TransH, TransR and PTransE](https://github.com/thunlp/KG2E)\n- [【论文:深度学习NLP的可视化理解】《Visualizing and Understanding Neural Models in NLP》J Li, X Chen, E Hovy, D Jurafsky (2015) ](https://github.com/jiweil/Visualizing-and-Understanding-Neural-Models-in-NLP)\n- [Links to the implementations of neural conversational models for different frameworks(seq2seq chatbot links)](https://github.com/nicolas-ivanov/seq2seq_chatbot_links)\n- [awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning)\n- [Awesome Tensorflow Implementations](https://github.com/TensorFlowKR/awesome_tensorflow_implementations)\n- [Awesome Recurrent Neural Networks](https://github.com/kjw0612/awesome-rnn)\n- [Awesome Reinforcement Learning](https://github.com/aikorea/awesome-rl)\n\n\n\u003cA name=\"people\"\u003e\n##People\n-[carpedm20](https://github.com/carpedm20)\n\n","created_at":"2026-02-17T22:01:13.602Z","updated_at":"2026-04-14T06:00:38.202Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["Uncategorized"],"sub_categories":["Uncategorized"],"projects_url":"https://awesome.ecosyste.ms/api/v1/lists/binbinbian%2Fawesome-code/projects"}