Boost Prophet for Forecasting: Easy Hyperparameter Optimization (code)

Prophet is a forecasting model developed by Facebook for time series analysis. It is designed to handle time series data with daily observations that display patterns such as trends, seasonality, and holidays. Prophet is particularly useful for predicting time series data with strong seasonal patterns and multiple seasonality.
We will look into tuning the prophet model through a very complex search space.
Code: colab.research...
Blog: / tuning-parameters-of-p...
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[@priyancashukla]

Super fast and accurate than in-built cross validation. This video deserves more views!!!

[@MachineLearningSchool]

Code: colab.research.google.com/drive/1Rjv3UBt_gsuOlkWlUW93TlG8BeYhtXKT?usp=sharing

[@MachineLearningSchool]

Blog post: medium.com/@sandha.iitr/tuning-parameters-of-prophet-for-forecasting-an-easy-approach-in-python-8c9a6f9be4e8

[@Sameerkang-xz3ck]

Forecasting is so much in demand. Nice video and work

[@nesltime3738]

Thanks for sharing this 😀

[@mandeepusakaur]

Cool work

[@gurdeepsingh-kn9ut]

Bro good luck 😊

[@aradhanarana9592]

Nice code but each parameter explanation is missing

[@pkrfernando2429]

Amazing man, how do you suggest using cross validation with this model?