Time Series Modeling - BKJackson/BKJackson_Wiki GitHub Wiki
Tutorials
An End-to-End Project on Time Series Analysis and Forecasting with Python - July 8, 2018
11 Classical Time Series Forecasting Methods in Python (Cheat Sheet) - Jason Brownlee, July 1, 2020
How to Convert a Time Series to a Supervised Learning Problem in Python - Jason Brownlee, Aug 21, 2019
A Step-by-Step Guide to Calculating Autocorrelation and Partial Autocorrelation - How to calculate the ACF and PACF values from scratch in Python
GluonTS - Time Series Modeling in Python
GluonTS
GluonTS - Extended Forecasting Tutorial
TimeSeriesAI - tsai
tsai github home
tsai documentation
Neural Network Approaches
Nixtla Neural Forecast - Scalable and user friendly neural 🧠 forecasting algorithms.
Signal denoising using RNNs in PyTorch
Neural Ordinary Differential Equations PDF
Liquid Time Constant Networks - Github
Neural Circuit Policies for PyTorch and TensorFlow - Github
Discrete-Event Continuous-Time Recurrent Nets PDF
Liquid Neural Network Foundation Models
Facebook Prophet
Delorean
Delorean - a python library for enhancing DateTime. Delorean stands on the shoulders of giants pytz and dateutil. Delorean docs
from delorean import Delorean
d = Delorean()
d = d.shift('US/Eastern')
return d
Arrow
Arrow - Better dates and times for Python. Python library that offers a sensible and human-friendly approach to creating, manipulating, formatting and converting dates, times and timestamps.
PyFlux
PyFlux docs - a library for time series analysis and prediction.
PyTZ
PyTZ docs - World timezone definitions for python
Cross-validation for time series
Cross-validation for time series
R code for the time series plots - Gist
StatsModels - statistics in Python
Sequence learning
hmmlearn - set of algorithms for unsupervised learning and inference of Hidden Markov Models
seqlearn - sequence classification toolkit for Python, for supervised learning of HMMs and similar models
Bayesian Approaches
Bayesian Structural Time Series - Proposed by Scott and Varian in 2013, Bayesian structural time series is a powerful set of methods that cover a large class of time series models using the State Space representation of time series and Bayesian statistics.
CommPy - Digital Communication with Python - Includes turbo decoder
Plotting Trellis Diagrams with CommPy in Python
The Viterbi Algorithm - Illustrated!
Books with code
Forecasting: Principles and Practice - By Rob J Hyndman and George Athanasopoulos, online text with R code