Scalable and user friendly neural 🧠 forecasting algorithms.
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Updated
May 28, 2024 - Python
Scalable and user friendly neural 🧠 forecasting algorithms.
PyTorch based Probabilistic Time Series forecasting framework based on GluonTS backend
Awesome Easy-to-Use Deep Time Series Modeling based on PaddlePaddle, including comprehensive functionality modules like TSDataset, Analysis, Transform, Models, AutoTS, and Ensemble, etc., supporting versatile tasks like time series forecasting, representation learning, and anomaly detection, etc., featured with quick tracking of SOTA deep models.
Snapchat-like filters, AR lenses, and real-time facial animations.
DeepAR SDK for Android example project
Time-Series models for multivariate and multistep forecasting, regression, and classification
Time Series Forecasting for the M5 Competition
DeepAR SDK for iOS example project
Dataiku DSS plugin to automate time series forecasting with Deep Learning and statistical models 📈
Video call using Agora.io SDK with face masks provided by DeepAR SDK
Video call using Vonage SDK with face masks provided by DeepAR SDK
Video call using Agora.io SDK with face masks provided by DeepAR SDK
DeepAR SDK for iOS example project
How to apply face filter on the photo loaded from gallery using DeepAR SDK
Arima, Sarima, LSTM, Prophet, DeepAR, Kats, Granger-causality, Autots
How to apply face filter on the photo loaded from gallery using DeepAR SDK
multivariate time series
Julia DeepAR implementation
Udacity Machine Learning Engineer Nanodegree Capstone Project
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