gccrpm

Pinned Repositories

3d
Three.js 3D项目，包含冰墩墩🐼、数字城市🏙、3D人像👤、车模展示🚗、塞尔达传说🗡等一些3D趣味演示页面，持续优化中...访问链接如下👇
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3DMaterials
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BookRecSys
图书推荐系统
Language:TSQL1120
cdmf
Hicss best paper nominated: A Deep Learning Model based on Convolutional and Dense-layer Matrix Factorization for Context-Aware Recommendation
Language:Python1 1 02
deep_learning-1
Basic Deep Learning
Language:Python36 2 015
knowledge_extraction
Chinese Open Entity Relation Extraction
Language:Python8 1 03
Recommender-System-for-Movies-using-Boltzmann-Machine
From Amazon product suggestions to Netflix movie recommendations - good recommender systems are very valuable in today's World. And specialists who can create them are some of the top-paid Data Scientists on the planet. I work on a dataset that has exactly the same features as the Netflix dataset: plenty of movies, thousands of users, who have rated the movies they watched. The ratings go from 1 to 5, exactly like in the Netflix dataset, which makes the Recommender System more complex to build than if the ratings were simply “Liked” or “Not Liked”. Final Recommender System will be able to predict the ratings of the movies the customers didn’t watch. Accordingly, by ranking the predictions from 5 down to 1, your Deep Learning model will be able to recommend which movies each user should watch. Creating such a powerful Recommender. Our f model Deep Belief Networks, complex Boltzmann Machines that will be covered for recommender system. The list of movies will be explicit so simply need to rate the movies you already watched, input your ratings in the dataset, execute model and voila! The Recommender System tell you exactly which movies you would love one night you if are out of ideas of what to watch on Netflix!
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Red-Things
IOT(internet of things) platform based on Node-Red, Easy but very useful to built a iot system
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stock-knowledge-graph
one stock knowledge graph project
Language:Python1 2 00
StockPricePredictionFromFinancialFilings
Stock Price Predictions from Financial Statements using Machine Learning and Deep Learning algorithms augmented with Knowledge Graph Embeddings
Language:Jupyter Notebook1 2 00

gccrpm's Repositories

gccrpm/attention
some attention implements
Language:Python1 0
gccrpm/Autochecker4Chinese
中文文本错别字检测以及自动纠错 / Autochecker & autocorrecter for chinese
Language:Jupyter Notebook
gccrpm/book_recommendation
This is a book recommendation system with tensorflow and python3.6
Language:Python
gccrpm/ChineseSTS
中文文本语义相似度（Chinese Semantic Text Similarity）语料库建设
gccrpm/correction
Chinese "spelling" error correction
Language:C++
gccrpm/DDIExtraction
Detecting drug-drug interaction (DDI) has become a vital part of public health safety. This project is an implementation of NLP based approach for such relation extraction between entities.
Language:Python
gccrpm/dnn_ctr
The framework to deal with ctr problem。The project contains FNN,PNN,DEEPFM, NFM etc
Language:Python
gccrpm/entity-relation-extraction
A TensorFlow implementation of the paper _End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures_ (https://www.aclweb.org/anthology/P16-1105).
Language:Python
gccrpm/JointEntityAndRelationExtraction
Language:Python
gccrpm/KnowledgeGraph
知识图谱车音工作项目
gccrpm/LSTM-ER
Implementation of End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures in ACL2016.
Language:C++
gccrpm/Market-Trend-Prediction
This is a project of build knowledge graph course. The project leverages historical stock price, and integrates social media listening from customers to predict market Trend On Dow Jones Industrial Average (DJIA).
gccrpm/Movie-Recommendation-System
Our Deep Learning Model will predict which user is going to like which movie using the recommendation system using Boltzmann Machine
Language:Python
gccrpm/movie_recommender
MovieLens based recommender system.使用MovieLens数据集训练的电影推荐系统。
Language:Jupyter Notebook1 0
gccrpm/Music-Recommendation-System-Kaggle-ML-Challenge-
Designed a classifier using various models such as Naïve bayes, SVM, NN, Deep learning, LGBM, XGBoost, etc. Performed pre-processing of data and applied k-fold cross-validation. Secured Top 100 position on Kaggle competition leaderboard with an accuracy of 69.62%.
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gccrpm/NER
基于tensorflow深度学习的中文的命名实体识别
Language:Python
gccrpm/NN_NER_tensorFlow
Implementing , learning and re implementing "End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF" in Tensorflow
Language:Python
gccrpm/PageRank
Implementation of the PageRank algorithm
Language:Python
gccrpm/recsys-2017-online-learning-tutorial
gccrpm/Relation-Classification
Relation Classification using LSTM Tree between two given entities using Tensorflow
Language:Jupyter Notebook
gccrpm/sequence-based-recommendations
Language:Python
gccrpm/Serving-TensorFlow-Model
Train, save and serve a linear regression model in TensorFlow
Language:Python1 0
gccrpm/SparkLearning
Learning Apache spark,including code and data .Most part can run local.
Language:Scala
gccrpm/TensorFlow-Java-Examples
Examples of Invoking TensorFlow from Java
Language:Java1 0
gccrpm/tf-rnn-attention
Tensorflow implementation of attention mechanism for text classification tasks.
Language:Python
gccrpm/tfrecommender
A TensorFlow recommendation algorithm and framework in Python.
Language:Python
gccrpm/Transformer-in-generating-dialogue
An Implementation of 'Attention is all you need' with Chinese Corpus
Language:Python
gccrpm/triplets-extraction
Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme
Language:Python
gccrpm/wooyun_public
乌云公开漏洞、知识库爬虫和搜索 crawl and search for wooyun.org public bug(vulnerability) and drops
Language:PHP
gccrpm/zh-NER-TF
A very simple BiLSTM-CRF model for Chinese Named Entity Recognition 中文命名实体识别 (TensorFlow)
Language:Python