The Datapred blog

On machine learning, time series and how to use them.

8 ways machine learning can boost your buying process

Staying ahead of procurement change

How raw material buyers can contribute to emission reduction

5 findings about contextual data and raw material price analysis

Covid-19 and raw materials - The many shapes of instability

Datapred raises Series A from JOIN Capital

Prediction and prescription - Continuous intelligence twins (Part 2/2)

Prediction and prescription - Continuous intelligence twins (Part 1/2)

The next big thing (in business intelligence)

Stop stacking, start aggregating

Datapred wins Airbus’s 2019 time series modeling challenge

Datapred named a 2019 Cool Vendor in Sourcing & Procurement Applications by Gartner

Direct material procurement: beating the market is not the point

Custom loss functions - What they are and why you need them

Productizing machine learning models - What is required?

How should you handle seasonality?

Advanced cross validation tips for time series

Best practices for bulletproof time series modeling

A better Facebook Prophet

Random Forest for predictive maintenance: Try harder

Machine learning for demand prediction: what works and what doesn’t

The basics of backtesting

The problem with deep learning and time series

What is time series, and why is it special?

Recent Posts

Topics

see all

Subscribe