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: Machine Learning Frameworks · Probabilistic time series modeling in Python
Section: Time Series Analysis · Python - vProbabilistic time series modeling in Python.
(label: good first issue) PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing.
(formerly known as pytorch-transformers and pytorch-pretrained-bert) provides state-of-the-art general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet, CTRL...) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in…
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.
Scikit-learn is a powerful machine learning library that provides a wide variety of modules for data access, data preparation and statistical model building.
General purpose gradient boosting on decision trees library with categorical features support out of the box. It is easy to install, contains fast inference implementation and supports CPU and GPU (even multi-GPU) computation.
High-level, beginner-friendly API that now runs on multiple backends (TensorFlow, JAX, PyTorch). Perfect for rapid experimentation.
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.