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The Datapred blog
On machine learning, time series and how to use them.
The 12 time windows of Procurement
Datapred announces the move of its Paris office to Maison RaiseLab
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?
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