scikit-learn VS Prophet

Compare scikit-learn vs Prophet and see what are their differences.


scikit-learn: machine learning in Python (by scikit-learn)


Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth. (by facebook)
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scikit-learn Prophet
24 45
48,142 13,740
0.8% 1.6%
9.9 7.6
3 days ago 27 days ago
Python Python
BSD 3-clause "New" or "Revised" License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.


Posts with mentions or reviews of scikit-learn. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-11-13.


Posts with mentions or reviews of Prophet. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing scikit-learn and Prophet you can also consider the following projects:

Keras - Deep Learning for humans

tensorflow - An Open Source Machine Learning Framework for Everyone

Surprise - A Python scikit for building and analyzing recommender systems

xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

gensim - Topic Modelling for Humans

greykite - A flexible, intuitive and fast forecasting library


MLflow - Open source platform for the machine learning lifecycle

darts - A python library for easy manipulation and forecasting of time series.

sktime - A unified framework for machine learning with time series