tuanlda78202/mlp
SAIMDB - ML Project S2T2, DSAI HUST
This project helps evaluate and compare different machine learning and deep learning methods for classifying movie reviews. It takes raw text reviews as input and determines whether each review expresses a positive or negative sentiment. Film critics, market researchers in the entertainment industry, or anyone interested in understanding audience perception from text reviews would find this useful.
No commits in the last 6 months.
Use this if you need to automatically categorize a large volume of movie reviews as either positive or negative.
Not ideal if you need to analyze sentiment for product reviews outside of movies or require a more nuanced sentiment score beyond positive/negative.
Stars
10
Forks
2
Language
Jupyter Notebook
License
GPL-3.0
Category
Last pushed
Jul 20, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/tuanlda78202/mlp"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
neural-data-science/NESC_3505_textbook
Textbook for NESC 3505, Neural Data Science, at Dalhousie University
GeostatsGuy/MachineLearningCourse
My graduate level machine learning course, including student machine learning projects.
snrazavi/Machine_Learning_2018
Codes and Project for Machine Learning Course, Fall 2018, University of Tabriz
gerdm/prml
Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine...
tuanavu/coursera-university-of-washington
University of Washington