Film review classification

Overview

Film review classification

Решение задачи классификации отзывов на фильмы на положительные и отрицательные с помощью рекуррентных нейронных сетей

1. Задача:

Для набора отзывов на фильмы из Internet Movie Database (IMDB) необходимо научиться классифицировать отзывы на положительные и отрицательные

2. Технологии:

  • Python 3
  • Pytorch
  • Numpy
  • Torchtext
  • Google Colab

3. Модель:

  • Embedding-слой для представления индексов в отзыве в качестве векторов
  • RNN/GRU-ячейки для обработки текста (рекуррентные нейронные сети)
  • Linear + SoftMax слои для классификации текста

4. Результаты:

Точность предсказаний (метрика accuracy): 86%

You might also like...
Official implementation of AAAI-21 paper
Official implementation of AAAI-21 paper "Label Confusion Learning to Enhance Text Classification Models"

Description: This is the official implementation of our AAAI-21 accepted paper Label Confusion Learning to Enhance Text Classification Models. The str

For holding anime-related object classification and detection models

Animesion An end-to-end framework for anime-related object classification, detection, segmentation, and other models. Update: 01/22/2020. Due to time-

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

Learning embeddings for classification, retrieval and ranking.
Learning embeddings for classification, retrieval and ranking.

StarSpace StarSpace is a general-purpose neural model for efficient learning of entity embeddings for solving a wide variety of problems: Learning wor

MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification

MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification

Implementation of TimeSformer, a pure attention-based solution for video classification
Implementation of TimeSformer, a pure attention-based solution for video classification

TimeSformer - Pytorch Implementation of TimeSformer, a pure and simple attention-based solution for reaching SOTA on video classification.

Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch
Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch

Transformer in Transformer Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image c

Ready-to-use code and tutorial notebooks to boost your way into few-shot image classification.

Easy Few-Shot Learning Ready-to-use code and tutorial notebooks to boost your way into few-shot image classification. This repository is made for you

Owner
Nikita Dukin
Nikita Dukin
Convenient tool for speeding up the intern/officer review process.

icpc-app-screen Convenient tool for speeding up the intern/officer applicant review process. Eliminates the pain from reading application responses of

null 1 Oct 30, 2021
Python Algorithm Interview Book Review

파이썬 알고리즘 인터뷰 책 리뷰 리뷰 IT 대기업에 들어가고 싶은 목표가 있다. 내가 꿈꿔온 회사에서 일하는 사람들의 모습을 보면 멋있다고 생각이 들고 나의 목표에 대한 열망이 강해지는 것 같다. 미래의 핵심 사업 중 하나인 SW 부분을 이끌고 발전시키는 우리나라의 I

SharkBSJ 1 Dec 14, 2021
A repository for storing njxzc final exam review material

文档地址,请戳我 ?? ?? ?? ☀️ 1.Reason 大三上期末复习软件工程的时候,发现其他高校在GitHub上开源了他们学校的期末试题,我很受触动。期末

GuJiakai 2 Jan 18, 2022
Stock-history-display - something like a easy yearly review for your stock performance

Stock History Display Available on Heroku: https://stock-history-display.herokua

LiaoJJ 1 Jan 7, 2022
Implement face detection, and age and gender classification, and emotion classification.

YOLO Keras Face Detection Implement Face detection, and Age and Gender Classification, and Emotion Classification. (image from wider face dataset) Ove

Chloe 10 Nov 14, 2022
Simple-Image-Classification - Simple Image Classification Code (PyTorch)

Simple-Image-Classification Simple Image Classification Code (PyTorch) Yechan Kim This repository contains: Python3 / Pytorch code for multi-class ima

Yechan Kim 8 Oct 29, 2022
Image Classification - A research on image classification and auto insurance claim prediction, a systematic experiments on modeling techniques and approaches

A research on image classification and auto insurance claim prediction, a systematic experiments on modeling techniques and approaches

null 0 Jan 23, 2022
Hl classification bc - A Network-Based High-Level Data Classification Algorithm Using Betweenness Centrality

A Network-Based High-Level Data Classification Algorithm Using Betweenness Centr

Esteban Vilca 3 Dec 1, 2022
Web-interface + rest API for classification and regression (https://jeff1evesque.github.io/machine-learning.docs)

Machine Learning This project provides a web-interface, as well as a programmatic-api for various machine learning algorithms. Supported algorithms: S

Jeff Levesque 252 Dec 11, 2022
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

CatBoost 6.9k Jan 4, 2023