Prophet
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth. (by facebook)
H2O
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc. (by h2oai)
| Prophet | H2O | |
|---|---|---|
| 225 | 11 | |
| 19,384 | 7,223 | |
| 0.7% | 0.7% | |
| 7.1 | 8.8 | |
| about 1 month ago | about 20 hours ago | |
| Python | Jupyter Notebook | |
| MIT License | Apache License 2.0 |
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.
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.
Prophet
Posts with mentions or reviews of Prophet.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2025-05-19.
- Prophet: Automatic Forecasting Procedure (2023)
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AI and Time Series Data: Harnessing the Power of Temporal Insights
As we prepare for the next phase in AI evolution, embracing decentralized approaches and synthetic data generation will be essential. Developers are encouraged to explore technologies like TensorFlow, Prophet, and platforms hosted on Ocean Protocol and License Token for further exploration. Additionally, more detailed discussions on these topics can be found in in-depth Dev.to posts such as Apache Mahout: A Deep Dive into Open Source Innovation and Funding Models.
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AI and Time Series Data: Harnessing Temporal Insights in a Digital Age
Emerging trends like decentralized data markets, synthetic time series generation, and enhanced NFT-based monetization models underline the vibrant future awaiting AI-driven predictive analytics. For developers and industry leaders, familiarizing yourself with tools like TensorFlow, Prophet, and Nixtla’s TimeGPT is crucial to stay ahead in this dynamic field.
- TimesFM (Time Series Foundation Model) for time-series forecasting
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Moirai: A Time Series Foundation Model for Universal Forecasting
https://facebook.github.io/prophet/
"Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well."
- prophet: NEW Data - star count:17116.0
- prophet: NEW Data - star count:17082.0
- Facebook Prophet: library for generating forecasts from any time series data
- prophet: NEW Data - star count:16196.0
H2O
Posts with mentions or reviews of H2O.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-07-12.
-
H2O: Your New Best Friend for Scalable Machine Learning
View the Project on GitHub
-
Really struggling with open source models
I would use H20 if I were you. You can try out LLMs with a nice GUI. Unless you have some familiarity with the tools needed to run these projects, it can be frustrating. https://h2o.ai/
- Democratizing Large Language Models
- Interview AI Coach - by email
-
Top 10+ OpenAI Alternatives
H2O.ai
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Best machine learning framework(s) for production
Thanks for the input. To clarify, I am more focused on choosing the modeling framework(s) that makes the most sense to use for future production. For example, is h2o.ai a good framework for training models for later deployment (through something like elastic beanstalk, Flask API's etc.)? I came across a number of mentions of Tensorflow, however it is focused on neural nets while I also want to use classic models such as random forests, etc.
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Time Series Analysis - Too Narrow a Dataset / Feature Set?
I've also initialised an instance of H2O.ai, so I can parse into the server each product, by store, segmented. It can then train the models, determine which model is the most performant, and then save it. Because the variability of different product SKU, at different hospitals, is substantial.
- A Tiny Grammar of Graphics
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20+ Free Tools & Resources for Machine Learning
H2O.ai H2O is a deep learning tool built in Java. It supports most widely used machine learning algorithms and is a fast, scalable machine learning application interface used for deep learning, elastic net, logistic regression, and gradient boosting.
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Data Science Competition
H20
What are some alternatives?
When comparing Prophet and H2O you can also consider the following projects:
scikit-learn - scikit-learn: machine learning in Python
tensorflow - An Open Source Machine Learning Framework for Everyone
MLflow - Open source platform for the machine learning lifecycle
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
pycaret - An open-source, low-code machine learning library in Python