Datasheets, use cases and white papers on Datapred, machine learning and time series.

Direct material procurement - What to expect from machine learning

Machine learning creates new opportunities for commodity, energy and raw material buyers. This three-page datasheet describes the main benefits that Chief Procurement Officers can expect from machine learning.

  • Unified view of the market
  • Price forecasting
  • Better understanding of price risk
  • Better alignement with operations
  • Effective long-term planning
  • Broader hedging opportunities
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ML & Direct material procurement

Procurement - Whats required

Direct material procurement optimization - What's required?

Datapred for Procurement can shave 3-5% off your commodity, energy and raw material spend, year over year. This six-page datasheet discusses the main requirements for using Datapred:

  • Price and contextual data
  • Costs and constraints
  • Wiggle room
  • Basic technical stack
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Specificities of machine learning for time series

Why is time series modeling so different? This 22-page presentation is a detailed explanation of the three specificities of time series, and their consequences for the design of machine learning solutions.


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Specificities of Time Series Modeling-1

Datapred relevance

When should you use Datapred?

Datapred is a powerful modeling engine for continuous intelligence applications. This three-page datasheet describes when that modeling engine is particularly relevant.
  • Streaming data
  • Multiple models
  • Explainability
  • Production-ready
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Vital checklist for time series modeling

Applying machine learning to time series is tricky. Don't dive into your time series modeling project without checking this 3-page life-saving list first.


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Vital checklist