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PyCIL: A Python Toolbox for Class-Incremental Learning
A playbook for systematically maximizing the performance of deep learning models.
Official Implementation of IJCAI-ECAI-2022 1st Learning and Mining with Noisy Labels Challenge Runner-up "Noise-Robust Bidirectional Learning with Dynamic Sample Reweighting"
😎 An up-to-date & curated list of awesome semi-supervised learning papers, methods & resources.
A curated (most recent) list of resources for Learning with Noisy Labels
刷算法全靠套路，认准 labuladong 就够了！English version supported! Crack LeetCode, not only how, but also why.
Using Python, Javascript, Postgres and HTML built a retail dashboard containing interactive visualization and forecast generated by Facebook Prophet and other machine learning models. Grocery recom…
《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning
MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba. Full multimodal LLM Android App:[MNN-LLM-Android](./apps/Android/MnnLlmChat/READ…
📦 PyTorch based visualization package for generating layer-wise explanations for CNNs.
Code for paper: Simple and Robust Loss Design for Multi-Label Learning with Missing Labels
推荐系统入门教程，在线阅读地址：https://datawhalechina.github.io/fun-rec/