Awesome Data Analysis
Section: Tools · A Python toolkit for probabilistic time series modeling, built on MXNet.
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Appears in 4 awesome lists
Probabilistic time series modeling with deep learning. Powers Amazon SageMaker forecasting with PyTorch and MXNet backends. Apache 2.0 licensed.
Section: Tools · A Python toolkit for probabilistic time series modeling, built on MXNet.
Section: 11. Specialized Domains · Probabilistic time series modeling with deep learning. Powers Amazon SageMaker forecasting with PyTorch and MXNet backends. Apache 2.0 licensed.
Section: Time Series Analysis · Python - vProbabilistic time series modeling in Python.
Section: Machine Learning Frameworks · Probabilistic time series modeling in Python
Modern, comprehensive probabilistic programming framework in Python. Bayesian modeling with advanced MCMC sampling, variational inference, and seamless integration with ArviZ for visualization. Apache 2.0 licensed.
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Visualize time series (from sources such as: MQTT, Websockets, ZeroMQ, UDP, etc., supports data formats such as JSON, CBOR, BSON, Message Pack, etc.). It is a fast, powerful and intuitive cross-platform tool.
Quantitative finance: multi-agent AI hedge fund trading system featuring native JevLLM integration to execute fast typed decisions without parsing fragility.
FAIR's next-generation research platform for object detection and segmentation. It is a ground-up rewrite of the previous version, Detectron, and is powered by the PyTorch deep learning framework.
Python library for automatic extraction of relevant features from time series.