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Implementations, Pre-training Code and Datasets of Large Time-Series Models
[NeurIPS 2025 Spotlight] Enhancing Time Series Forecasting through Selective Representation Spaces: A Patch Perspective
主要记录大语言大模型(LLMs) 算法(应用)工程师相关的知识及面试题
A Fair and Scalable Time Series Forecasting Benchmark and Toolkit.
Efficient token-bucket-based rate limiter package.
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
Machine Learning Engineering Open Book
每个人都能看懂的大模型知识分享,LLMs春/秋招大模型面试前必看,让你和面试官侃侃而谈
这是一个使用RTP协议流视频的Android程序,你可以将其用作服务器的IP摄像头,进行云端的实时监控、目标检测、动作识别等功能。
编写一个简单的字符设备驱动程序,以内核空间模拟字符设备,完成对该设备的打开,读写和释放操作,并编写聊天程序实现对该设备的同步和互斥操作。
GeeRPC是一个从头实现 Go 语言官方的标准库 net/rpc的RPC框架,并新增了协议交换(protocol exchange)、注册中心(registry)、服务发现(service discovery)、负载均衡(load balance)、超时处理(timeout processing)等特性。
深度学习100例、深度学习DL、图片分类、目标识别、目标检测、自然语言处理nlp、文本分类、TensorFlow、PyTorch
Collection of notebooks for time series analysis
Time series Timeseries Deep Learning Machine Learning Python Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
Scalable and user friendly neural 🧠 forecasting algorithms.
An offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arxiv.org/abs/2211.14730
[PVLDB 2024 Best Paper Nomination] TFB: Towards Comprehensive and Fair Benchmarking of Time Series Forecasting Methods
A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputatio…
Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70%
极客时间:LangChain实战课 - 这是LangChain框架早期设计的一系列重点模块的直接而清晰的示例和讲解。随着LangChain的快速演进,有些代码需要安装新的版本进行迭代。希望大家在快速浏览课程概念(仍有价值)的同时,自行学习LangChain最新的代码和进展。
TGwiki - Telegram知识库,由TGNAV打造的高质量Telegram知识库,帮助用户更科学地使用Telegram。
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A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals.