There are often multiple dimensions to consider: capacity requirements, pricing, segmentation, services, delivery times, and distribution channels (i.e. where/how the product/service will be sold and how it will be shipped).

The multi-decision problem is typically high dimensional since the number of decision variables might be quite large and each decision affects the others.

The alternative way of tackling this problem is shuffling the data around and applying a statistical algorithm to each dimension (or sub-part) of the data. However, each different algorithm for each decision variable is computationally intensive, and users cannot run the algorithm on their own.

Google AutoML is a free machine learning API for solving multi-dimensional problems.

Read the documentation here.
https://lnkd.in/dRhVe-Xc

Google AutoML takes your inputs and builds a model to make predictions for you.

Build your predictive models using Google AutoML and Chainer today.

Chainer AutoML uses your Chainer models and generates predictions from a single Chainer graph. Google Prediction API is a web service that gives users access to legacy machine learning APIs such as Multinomial Log-Reg.

Using Google Prediction API you still have to write model code, so you need to get used to writing code in Python. Using Chainer AutoML you don’t have to write any code at all!

#python #data #machinelearning #multidimensional #decisionmaking #decisionintelligence #decisionpipeline #google