chai_py
Prophet
| chai_py | Prophet | |
|---|---|---|
| 3 | 221 | |
| 60 | 17,767 | |
| - | 0.6% | |
| 0.0 | 6.2 | |
| about 1 year ago | 3 days ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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.
chai_py
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WHAAATTT! Since when the bots can do this? How to use it?
The package is here: https://github.com/chai-research/chai_py Quoted directly from the documentation: "The bot response accepts markdown and so you can include an image like "
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Developer Docs
Worth noting the code is not open source. As you can see here, the inside of the functions are empty : https://github.com/chai-nexus/chai_py/blob/main/chai_py/chai_bot.py But it may be possible to get its real content with the inspect module
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Is there an updated Python API in the works by chance?
The latest release is 0.4.0 from about a year ago. This looks abandoned ( https://github.com/chai-nexus/chai_py and https://pypi.org/project/chaipy/ ) and doens't work for even simply operations like retrieving the bot list. (yes with authentication of course; I have 1 bot deployed and that call bombs with a 500 status claiming "Payload is too large")
Prophet
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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
- prophet: NEW Data - star count:15889.0
What are some alternatives?
scikit-learn - scikit-learn: machine learning in Python
tensorflow - An Open Source Machine Learning Framework for Everyone
darts - A python library for user-friendly forecasting and anomaly detection on time series.
MLP Classifier - A handwritten multilayer perceptron classifer using numpy.
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
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
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.
greykite - A flexible, intuitive and fast forecasting library
adaptive - :chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions
MLflow - Open source platform for the machine learning lifecycle