Home
Procurement
Modeling engine
Other use cases
Integrations
Resources
Blog
Downloads
Recruiting
Contact
The Datapred blog
On machine learning, time series and how to use them.
The next big thing
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
backtest
(3)
backtesting
(5)
constraint optimization
(2)
continuous intelligence
(3)
cool vendor
(1)
cross validation
(1)
decision management
(4)
deep learning
(1)
demand prediction
(2)
direct materials
(2)
facebook
(1)
financial economics
(1)
financial markets
(1)
gartner
(1)
holt-winters
(1)
LSTM
(1)
machine learning
(12)
modeling
(3)
neural networks
(1)
operations research
(1)
predictive analysis
(6)
predictive maintenance
(2)
procurement
(2)
productization
(2)
Prophet
(1)
random forest
(1)
raw materials
(2)
seasonality
(1)
sequential aggregation
(2)
sequential data
(2)
stacking
(1)
streaming data
(2)
time series
(9)
see all
Subscribe
