Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
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Updated
Nov 8, 2023 - Python
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data
A collection of AWESOME things about domian adaptation
Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
The next generation deep reinforcement learning tookit
A library for transfer learning by reusing parts of TensorFlow models.
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.
Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2021)。
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with …
EasyNLP: A Comprehensive and Easy-to-use NLP Toolkit
Libraries for applying sparsification recipes to neural networks with a few lines of code, enabling faster and smaller models
FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai
🦄 State-of-the-Art Conversational AI with Transfer Learning
🏡 Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
Best transfer learning and domain adaptation resources (papers, tutorials, datasets, etc.)
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