Time Series Analysis with Python Cookbook, Second Edition - Published by Packt
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Updated
Feb 12, 2026 - Jupyter Notebook
Time Series Analysis with Python Cookbook, Second Edition - Published by Packt
Nixtla time series forecasting plugins for Claude Code. StatsForecast, MLForecast, and NeuralForecast integrations with agent skills.
Time-series forecasting platform with AutoModels, exogenous analysis, resource monitoring and experiment management.
Lottery time-series feature engineering platform for NeuralForecast AutoModels.
PatchTST 论文对齐复现:UCI 家庭负荷 L=168→H=24 直接多输出预测,滚动评估 + 泄漏审查 + 论文声称逐条核对
Benchmarking a stacked LSTM, custom Transformer, and a Temporal Fusion Transformer on forecasting tasks using hourly Bitcoin data.
Probabilistic day-ahead LMP forecasting for 8–12 PJM zones using Temporal Fusion Transformer and a frozen semantic-embedding fusion branch. Produces P10/P50/P90 hourly forecasts, attention and variable-importance visualizations, and fusion-gate diagnostics.
Day-ahead electricity price forecasting for the German bidding zone, under a strict gate-closure information constraint. The most accurate model turns out to be one that cannot run.
Minimal reference implementation for running Lightning and NeuralForecast on Intel GPU via native PyTorch XPU.
Research and operations platform for statistically rigorous lottery forecasting experiments across six games.
Dashboard Analitik Time Series dengan NHITS
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