Stars
A use-case focused tutorial for time series forecasting with python
Probabilistic time series modeling in Python
Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git, Kubernetes, Terraform, OpenStack, SQL, NoSQL, Azure, GCP, DNS, Elastic, Network, Virtualization. DevOps Interview Questions
ShellCheck, a static analysis tool for shell scripts
An easy to use and powerful chaos engineering experiment toolkit.（阿里巴巴开源的一款简单易用、功能强大的混沌实验注入工具）
Overview of the peaks dectection algorithms available in Python
[Maintenance mode] Serverless Status Page System
🚦 Cachet, the open-source, self-hosted status page system.
A statuspage generator that lets you host your statuspage for free on Github.
A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques
IPCCC 2018: Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder
WWW 2018: Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications
KDD 2019: Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network
Tool for producing high quality forecasts for time series data that has multiple 8000 seasonality with linear or non-linear growth.
Code from the Kubernetes in Action book
Code repository for Data Wrangling with Python (O'Reilly)
An Integrated Experimental Platform for time series data anomaly detection.
Fast and accurate cross-correlation over arbitrary time lags. Moved to:
A Python cross correlation command line tool for unevenly sampled time series
Comparing accuracy of two standard deep learning models like CNN and RNN on the human activity recognition dataset
Jupyter Notebook for Human Activity Recognition (HAR) with 1D Convolutional Neural Network in Python and Keras
Classification of Twitter Emotions using LSTM,biLSTM, CNN-LSTM and GRU
Using a CNN with Grated recurrent units and Time distributed wrappers over MNIST data