Time series forecasts are used to predict a future value or a classification at a particular point in time. Here’s a brief overview of their common uses and how they are developed. Industries from ...

XGBoost is a popular open source machine learning library that can be used to solve all kinds of prediction problems. Here’s how to use XGBoost with InfluxDB. XGBoost is an open source machine ...

Picture a single forecasting mistake triggering a cascade of negative consequences, such as surplus inventory, strained supplier relationships and disappointed customers. In today's world, accurate ...

The paper identifies three major areas in which AI is now vital. These include financial market prediction, macroeconomic ...

Researchers in China have applied a machine learning technology based on temporal convolutional networks in PV power forecasting for the first time. The new model reportedly outperforms similar models ...

Yet most demand forecasting systems today often produce disappointing results and significant forecast errors. The standard models found in these systems cannot easily identify trends in the data.

Automating through machine learning (ML) allowed Amazon.com to predict future demand for millions of products globally in seconds. Leaders at the multinational tech giant successfully reinvented their ...

The Covid-19 pandemic has proved that history no longer repeats itself when it comes to understanding consumer behavior. Demand forecasting systems have been ill-equipped to address disruptions to our ...