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💯2026年 网络工程师 (软考中级)备考资源库。 PC版免费刷题软件:https://ruankaodaren.com
整理一些书籍 ,包含 C&C++ 、git 、Java、Keras 、Linux 、NLP 、Python 、Scala 、TensorFlow 、大数据 、推荐系统、数据库、数据挖掘 、机器学习 、深度学习 、算法等。
🔥机器学习/深度学习/Python/大模型/多模态/LLM/deeplearning/Python/Algorithm interview/NLP Tutorial
深度学习面试宝典(含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向)
The easiest way to get started with LlamaIndex
Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
A modular graph-based Retrieval-Augmented Generation (RAG) system
The paper list of the 86-page SCIS cover paper "The Rise and Potential of Large Language Model Based Agents: A Survey" by Zhiheng Xi et al.
【Java面试+Java学习指南】 一份涵盖大部分Java程序员所需要掌握的核心知识。
Java 学习&面试指南(Go、Python 后端面试通用,计算机基础面试总结)。准备后端技术面试,首选 JavaGuide!
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
哈工大(本部)计算机专业研究生课程攻略 | HIT CS Postgraduate Guide
Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)
将Typora伪装成LaTeX的中文样式主题,本科生轻量级课程论文撰写的好帮手。This is a theme disguising Typora into Chinese LaTeX style.
Collection of generative models in Pytorch version.
[arXiv:2411.10023] "Model Inversion Attacks: A Survey of Approaches and Countermeasures"
FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs o…
FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai
A flexible Federated Learning Framework based on PyTorch, simplifying your Federated Learning research.
Implementation of SCAFFOLD: Stochastic Controlled Averaging for Federated Learning
PyTorch implementation of SCAFFOLD (Stochastic Controlled Averaging for Federated Learning, ICML 2020).
A framework for Privacy Preserving Machine Learning