FreqAI is an open-source project that allows for time-series forecasting via established machine learning algorithms, such as Reinforcement Learning, Decision Trees, and Neural Networks.
Built in Python, the core engine allows users to connect any open-source machine learning or data analysis library to create a custom system for adaptive modeling. We currently provide pre-configured base models for XGBoost, LightGBM, CatBoost, Tensorflow, and Stable Baselines and PyTorch.

DISCLAIMER FreqAI has gained such a strong reputation in the open-source machine learning community that it has become a target of imposter projects aimed at using the FreqAI name to offer cryptocurrencies. FreqAI is not affiliated with any cryptocurrency offerings. FreqAI is, and always will be, a not-for-profit, open-source project. FreqAI does not have a crypto token, FreqAI does not sell signals, and FreqAI does not have a domain besides the freqtrade documentation https://www.freqtrade.io/en/latest/freqai/. Please beware of imposter projects, and help us by reporting them to the official FreqAI discord server.

Flowdapt is an Emergent Methods project for large-scale adaptive modeling challenges. It is highly adaptable to handle customized workflows (plug-ins) in parallelized environments. The software comes equipped with industry standard machine learning methods such as classifiers, regressors, neural networks, reinforcement learning, outlier detection, data normalization, and much more.

Flowdapt builds on top of Dask, a high-throughput, cluster-compute base-layer that handles complex task scheduling and load balancing. Meanwhile, Flowdapt adds a REST API, built-in MLOps, automated adaptive modeling algorithms, and industry standard machine learning and outlier detection methods.

Flowdapt is built in Python, but is equipped with a well documented REST API geared for integration into external software written in any other language. Anyone can build their own plug-in, and Emergent Methods offers a variety of customizable template options, including open-source and proprietary examples such as weather forecast, finance market forecasts, and building automation.