pykale VS Meta-SelfLearning

Compare pykale vs Meta-SelfLearning and see what are their differences.

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! (by pykale)
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pykale Meta-SelfLearning
2 1
427 197
1.6% -
9.1 0.0
about 1 month ago over 1 year 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.

pykale

Posts with mentions or reviews of pykale. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-04-25.

Meta-SelfLearning

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

What are some alternatives?

When comparing pykale and Meta-SelfLearning you can also consider the following projects:

EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.

LFattNet - Attention-based View Selection Networks for Light-field Disparity Estimation

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

TextRecognitionDataGenerator - A synthetic data generator for text recognition

Multimodal-Toolkit - Multimodal model for text and tabular data with HuggingFace transformers as building block for text data

ORBIT-Dataset - The ORBIT dataset is a collection of videos of objects in clean and cluttered scenes recorded by people who are blind/low-vision on a mobile phone. The dataset is presented with a teachable object recognition benchmark task which aims to drive few-shot learning on challenging real-world data.

social-balance - A library-agnostic project for calculating exactly and efficiently social balance, based on the Aref, Mason and Wilson paper (https://arxiv.org/abs/1611.09030)

synthetic-computer-vision - A list of synthetic dataset and tools for computer vision

open_flamingo - An open-source framework for training large multimodal models.

fashion-mnist - A MNIST-like fashion product database. Benchmark :point_down:

jina - ☁️ Build multimodal AI applications with cloud-native stack

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