Transfer-Learning-Library VS transferlearning

Compare Transfer-Learning-Library vs transferlearning and see what are their differences.

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Transfer-Learning-Library transferlearning
1 1
3,150 12,867
2.2% -
6.9 7.8
about 1 month ago 9 days 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.

Transfer-Learning-Library

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

transferlearning

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

What are some alternatives?

When comparing Transfer-Learning-Library and transferlearning you can also consider the following projects:

TranAD - [VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.

zshot - Zero and Few shot named entity & relationships recognition

DeepLabCut - Official implementation of DeepLabCut: Markerless pose estimation of user-defined features with deep learning for all animals incl. humans

stackoverflow-better-stats - Better statistics about Stack Overflow's 2023 Developer Survey

CEPC - A domain adaptation model

PaddleHelix - Bio-Computing Platform Featuring Large-Scale Representation Learning and Multi-Task Deep Learning “螺旋桨”生物计算工具集

AdaTime - [TKDD 2023] AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data

awesome-artificial-intelligence-research - A curated list of Artificial Intelligence (AI) Research, tracks the cutting edge trending of AI research, including recommender systems, computer vision, machine learning, etc.

StyleDomain - Official Implementation for "StyleDomain: Efficient and Lightweight Parameterizations of StyleGAN for One-shot and Few-shot Domain Adaptation" (ICCV 2023)

TS-TCC - [IJCAI-21] "Time-Series Representation Learning via Temporal and Contextual Contrasting"

pytorch-adapt - Domain adaptation made easy. Fully featured, modular, and customizable.

Efficient-VDVAE - Official Pytorch and JAX implementation of "Efficient-VDVAE: Less is more"