Time series forecasting with PyTorch
$ npx skills add sktime/pytorch-forecastingAlternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
NeuralProphet: A simple forecasting package
Time series forecasting with PyTorch
$ npx skills add sktime/pytorch-forecastingProbabilistic time series modeling in Python
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$ npx skills add onnx/onnxMachine Learning Systems
$ npx skills add harvard-edge/cs249r_bookA python library for user-friendly forecasting and anomaly detection on time series.
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$ npx skills add google-deepmind/sonnetFlower: A Friendly Federated AI Framework
$ npx skills add flwrlabs/flowerStanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
$ npx skills add stanfordnlp/stanzaChronos: Pretrained Models for Time Series Forecasting
$ npx skills add amazon-science/chronos-forecastingGoogle DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
$ npx skills add google-deepmind/dm_controlA Python package for segmenting geospatial data with the Segment Anything Model (SAM)
$ npx skills add opengeos/segment-geospatialScalable and user friendly neural :brain: forecasting algorithms.
$ npx skills add Nixtla/neuralforecastHow to choose
Use an alternative when it has a clearer install path, higher trust score, fresher maintenance, or better platform fit for your current agent stack. Keep Neural Prophet if it already passes your workflow test and repository review.
Next step
Open the compare page, test the install commands in a sandbox, and check each repository before using a skill in production.