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Nov 16 • 7 tweets • 2 min read
Python has powerful time series libraries.
Case in point: skforecast
Let me explain:
Skforecast is a Python library for time series forecasting using machine learning models.
Skforecast works with any regressor compatible with the scikit-learn API, including popular options like LightGBM, XGBoost, CatBoost, Keras, and many others.
Nov 15 • 6 tweets • 2 min read
My favorite R package for ultra-fast exploratory analysis:
The R package is called correlationfunnel.
Yes, I built it.
Nov 14 • 9 tweets • 3 min read
The best beginner book on time series?
FPP: Forecasting Principles and Practice
Let's dive in:
Some may consider FPP the bible of time series.
I agree.
Start with FPP Version 2 or 3, and you won't go wrong.
This is what I like:
Nov 12 • 8 tweets • 2 min read
BEAST: A Bayesian Ensemble Algorithm for Change-Point Detection and Time Series Decomposition in R
Let's explore: 1. What is BEAST?
BEAST stands for Bayesian Estimator of Abrupt change, Seasonality, and Trend.
But what does that mean?
Nov 11 • 12 tweets • 3 min read
I used to struggle with working with Time Series.
After 10 years, I mastered it.
Then I spent 3 years making this R package so you can too:
The R package is timetk. I built it to make your life easier when working with Time Series: