A library to generate synthetic time series data by easy-to-use factors and generator

tobs - The Observability Stack for Kubernetes. Easy install of a full observability stack into a k8s cluster with Helm charts.

Hands-on labs for Amazon EKS

AWS EKS Kubernetes - Masterclass | DevOps, Microservices

T81-558: PyTorch - Applications of Deep Neural Networks @Washington University in St. Louis

An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

Merlion: A Machine Learning Framework for Time Series Intelligence

Probabilistic ML course 2023

A unified framework for machine learning with time series

A playbook for systematically maximizing the performance of deep learning models.

Forecasting: principles and practice in python

A unified framework for machine learning with time series

Probabilistic time series modeling in Python

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

This is an official implementation for "Are Transformers Effective for Time Series Forecasting?"

This Repository consists of code to run a correlation based feature subset selection technique for multivariate time series data called MSTS

Code for the ACL 2022 paper "Efficient Unsupervised Sentence Compression by Fine-tuning Transformers with Reinforcement Learning"

ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels