hierarchical-domain-adaptation VS Machine-Learning

Compare hierarchical-domain-adaptation vs Machine-Learning and see what are their differences.

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hierarchical-domain-adaptation Machine-Learning
1 1
32 0
- -
3.0 10.0
8 months ago over 2 years ago
Python Python
- 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.

hierarchical-domain-adaptation

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

Machine-Learning

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

What are some alternatives?

When comparing hierarchical-domain-adaptation and Machine-Learning you can also consider the following projects:

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

curves-intersection-with-gradient-descent - Plotting points that lie on the intersection of the given curves using gradient descent.

pykale - Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥PyTorch ecosystem. ⭐ Star to support our work!

LLM-Adapters - Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models"