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Prophet Alternatives
Similar projects and alternatives to Prophet
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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jj
Discontinued A Git-compatible VCS that is both simple and powerful [Moved to: https://github.com/jj-vcs/jj] (by martinvonz)
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MLflow
The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-quality AI applications while controlling costs and managing access to models and data.
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EdenSCM
Discontinued A Scalable, User-Friendly Source Control System. [Moved to: https://github.com/facebook/sapling]
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scalar
Scalar: A set of tools and extensions for Git to allow very large monorepos to run on Git without a virtualization layer (by microsoft)
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nixtla
TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.
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timesfm
TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
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sturdy
🐥 Sturdy is an open-source, real-time, version control platform for startups (https://getsturdy.com)
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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
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catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
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Prophet discussion
Prophet reviews and mentions
- Google's 200M-parameter time-series foundation model with 16k context
- 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
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A note from our sponsor - SaaSHub
www.saashub.com | 15 Jun 2026
Stats
facebook/prophet is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of Prophet is Python.