Utilities for Scoring and Assessing Predictions
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Updated
May 23, 2024 - R
Utilities for Scoring and Assessing Predictions
Scalable and user friendly neural 🧠 forecasting algorithms.
TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code 🚀.
E-Commerce Analytics and Forecasting Project
Monte Carlo simulator of price data written in Rust
This repository contains the development of a predictive AI tool aimed at forecasting crowds based on various data streams such as access tag check-ins, Wi-Fi usage, venue sales data, and reservations.
Predictive Modeling for Day-Ahead Pricing in the Colombian Electricity Market
Automated Machine Learning pipelines. Builds the Open Short Term Energy Forecasting package.
{mvgam} R 📦 to fit Dynamic Bayesian Generalized Additive Models for time series analysis and forecasting
A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputation, classification, clustering, forecasting, & anomaly detection on incomplete industrial (irregularly-sampled) multivariate TS with NaN missing values
The platform for customizing AI from enterprise data
A unified framework for machine learning with time series
A toolkit for machine learning from time series
Solution for modeling population size in different districts in Vilnius
Univariate and multivariate time series forecasting, with uncertainty quantification (Python & R)
Univariate and multivariate time series forecasting, with uncertainty quantification (Python & R)
Im Datensatz 'COVID-19-Hospitalisierungen' werden die aktuellen Zahlen der nach den Vorgaben des Infektionsschutzgesetzes - IfSG - erfassten hospitalisierten COVID-19-Fälle bereitgestellt.
The new version of the INAMHI GEOGLOWS portal, developed using Angular, Django, and Docker for enhanced scalability and performance.
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