The movielens dataset is taken from kaggle. The system is implemented in python programming language. The proposed work deals with the introduction of various concepts related to machine learning and recommendation system. In this work, various tools and techniques have been used to build recommender...
The movie plot dataset is already included. To get more information check https://www.kaggle.com/datasets/jrobischon/wikipedia-movie-plots Install the dependencies: npm install Open encode-single-movie-plot.js to see how to encode a single movie plot using TensorFlow library and its sentence ...
该资源是kaggle上通过电影的评论信息,判断用户当时的情绪。能够收集到电影对用户情绪的影响,挖掘信息可以更加合理指导电影的商业推广。
# Dataset has been used: * [Dataset link](https://www.kaggle.com/tmdb/tmdb-movie-metadata?select=tmdb_5000_movies.csv) # Concept used to build the model.pkl file : cosine_similarity 1 . Cosine Similarity is a metric that allows you to measure the similarity of the documents. 2 . ...
? It's worth mentionning that there are a **few dumps of Netflix** anonymized user tastes on kaggle, because they've organised a few competitions to improve their recommendation models. https://www.kaggle.com/netflix-inc/netflix-prize-data ? Online databases are largely white anglo-saxon ...
提交结果 练习地址:https://www.kaggle.com/c/sentiment-analysis-on-movie-reviews 相关博文: [Kaggle] Spam/Ham Email 75810 Text classification with TensorFlow Hub:Moviereviews This notebook classifiesmoviereviews as positive or negative using the text of the review...It uses the IMDB dataset that...
Movie-recommendation-system:协同过滤和深度学习 ###电影推荐系统(MovieLen) 运行Python3 download_dataset.py以下载movielens数据集 运行Python3 usercf.py以运行基于用户的协作过滤算法 运行Python3 itemcf.py以运行基于项目的协作过滤算法 运行Python3 dl/trainer.py训练深度学习模型并进行测试 ...
Netflix-Movie-Recommendation-System Netflix电影推荐系统 问题描述 Netflix提供了许多匿名评级数据,并且其预测准确度要比Cinematch在相同的训练数据集上可以达到的准确度高10%。 (准确性是对电影的预测收视率与后续实际收视率的匹配程度的度量。) 资料总览 数据来源: : 数据文件:combined_data_1.txt,combined_data_...
Here, we have used Python and flask Web framework (and different libraries) to build the Web application, and the dataset used is scrapped from IMDb's Web site and combined from different dataset available on Kaggle.Acharya, Soumya S.
ratings. The aim of this paper is to design and evaluate 'KNN algorithm and Collaborative Filtering algorithm' for producing movie recommendations. The dataset used in this paper is 'Movielens dataset' which is downloaded from Kaggle. The system was implemented using 'Python programming language'. ...