TIMDB VS Federated-Recommendation-Neural-Collaborative-Filtering

Compare TIMDB vs Federated-Recommendation-Neural-Collaborative-Filtering and see what are their differences.

TIMDB

The Indian Movie Database - supports content-based and collaborative filtering techniques (by pncnmnp)
movie-database bollywood indian-cinema movie-recommendation
Source Code
github.com
Suggest alternative
Edit details

Federated-Recommendation-Neural-Collaborative-Filtering

Federated Neural Collaborative Filtering (FedNCF). Neural Collaborative Filtering utilizes the flexibility, complexity, and non-linearity of Neural Network to build a recommender system. Aim to federate this recommendation system. (by AmanPriyanshu)
federated-learning neural-network recommender-system distributed-learning Federated iid movie-recommendation ncf neural-collaborative-filtering non-iid recommendation-engine recommendation-system collaborative-filtering Deep Learning deep-recommender-system recommendation-algorithms
Source Code
Suggest alternative
Edit details
InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
featured
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com
featured
TIMDB Federated-Recommendation-Neural-Collaborative-Filtering
1 2
35 25
- -
0.0 3.9
12 months ago about 1 year ago
Python Python
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

TIMDB

Posts with mentions or reviews of TIMDB. We have used some of these posts to build our list of alternatives and similar projects.

Federated-Recommendation-Neural-Collaborative-Filtering

Posts with mentions or reviews of Federated-Recommendation-Neural-Collaborative-Filtering. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing TIMDB and Federated-Recommendation-Neural-Collaborative-Filtering you can also consider the following projects:

cinemagoer - Cinemagoer is a Python package useful to retrieve and manage the data of the IMDb (to which we are not affiliated in any way) movie database about movies, people, characters and companies

torchrec - Pytorch domain library for recommendation systems

next-movie - Pick your next movie using Next.js 13

LT-OCF - LT-OCF: Learnable-Time ODE-based Collaborative Filtering, CIKM'21

MovieRecommender - 🎥 Movie Recommender AI System

federeco - implementation of federated neural collaborative filtering algorithm

PopCritic - Movies Reviewed by people, for people

disco - Recommendations for Ruby and Rails using collaborative filtering

perplex - A Movie Renamer for Plex Metadata

recommenders - Best Practices on Recommendation Systems

watch3r - Movie watchlist and journal app built with Vue 3 and Fauna DB. All future development of this project has moved to Codeberg.

LargeBatchCTR - Large batch training of CTR models based on DeepCTR with CowClip.

TIMDB vs cinemagoer Federated-Recommendation-Neural-Collaborative-Filtering vs torchrec TIMDB vs next-movie Federated-Recommendation-Neural-Collaborative-Filtering vs LT-OCF TIMDB vs MovieRecommender Federated-Recommendation-Neural-Collaborative-Filtering vs federeco TIMDB vs PopCritic Federated-Recommendation-Neural-Collaborative-Filtering vs disco TIMDB vs perplex Federated-Recommendation-Neural-Collaborative-Filtering vs recommenders TIMDB vs watch3r Federated-Recommendation-Neural-Collaborative-Filtering vs LargeBatchCTR