Forecasting

What can we learn from this contemporary problem?By far the best challenge regarding this forecasting problem was handling the huge outlier attributable to the pandemic together with the next instability attributable to it. Our...

Benchmarking Lag-Llama against XGBoostSomething that catches the attention in a short time is that prediction intervals are substantially smaller than those from the zero-shot version. Actually, the interval area is 188.69. With these prediction...

Time series and more specifically time series forecasting is a really well-known data science problem amongst professionals and business users alike.Several forecasting methods exist, which could also be grouped as statistical or machine learning...

Exploring Chronos: How foundational AI models are setting recent standards in predictive analyticsThis post was co-authored with Rafael Guedes.Time series forecasting has been evolving towards foundation models attributable to their success in other artificial...

Time series forecasting plays a significant role in crucial decision-making processes across various industries resembling retail, finance, manufacturing, and healthcare. Nevertheless, in comparison with domains like natural language processing and image recognition, the combination...

A latest age for time seriesGoogle just entered the race of foundation models for time-series forecasting.In August 2023, the time-series community was disrupted by the discharge of TimeGPT, Nixtla’s first foundation model for time...

Big Tech’s arrival on the weather forecasting scene just isn't purely based on scientific curiosity, reckons Oliver Fuhrer, the top of the numerical prediction department at MeteoSwiss, the Swiss Federal Office of Meteorology...

“Prediction could be very difficult, especially if it’s in regards to the future” — Yogi Berra , NY YankeesIn this text, we'll explore the rationale and execution of constructing a predictive time series model...