Building Transformer Models with PyTorch, by BPB Publications

人工智能实践：Tensorflow笔记

A collection of various deep learning architectures, models, and tips

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

[VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.

A professionally curated list of awesome resources (paper, code, data, etc.) on transformers in time series.

Mathematical derivation and pure Python code implementation of machine learning algorithms.

Notes about courses Dive into Deep Learning by Mu Li

Anomaly detection tutorial on univariate time series with an auto-encoder

Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE

Classical ML equations in Latex, helps paper and blog writing

Repo for the Deep Learning Nanodegree Foundations program.

主要存储Datawhale组队学习中“数据挖掘/机器学习”方向的资料。

Sequence modeling benchmarks and temporal convolutional networks

https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1

GRATIS: GeneRAting TIme Series with diverse and controllable characteristics

Repository containing notebooks of my posts on Medium

A set of CPU utilization traces from PlanetLab VMs collected during 10 random days in March and April 2011

proof of concept for a transformer-based time series prediction model

A large collection of system log datasets for AI-powered log analytics

Keras documentation, hosted live at keras.io

TODS: An Automated Time-series Outlier Detection System

This repository contains the code to generate timeseries prediction with the RNN family

Anomaly detection related books, papers, videos, and toolboxes

Anomaly detection

Pytorch🍊🍉 is delicious, just eat it! 😋😋

https://github.com/lyhue1991/eat_tensorflow2_in_30_days ， 对应的jupyter notebook版本