“AutoML” Parameter Search for Hierarchical Demand Forecasting Optimization

In general, machine learning approaches expose many options that affect performance and accuracy. “AutoML” (Automated ML) concerns problems of optimizing over such options. Forecasting demand of products that form a hierarchy raises this kind of challenge. We recently wrote a blog post about demand forecasting for hierarchical data. We listed several approaches to reconciling forecasts…


Introducing Microsoft Data Science Virtual Machine

Microsoft Data Science Virtual Machine (DSVM) is a custom virtual machine on Microsoft’s Azure cloud build specifically for doing data science. It’s a powerful data science development sandbox equipped with the most popular tools for data exploration and modelling. You can provision a DSVM with a few clicks on Microsoft Azure website, and within 10-20…


Demand forecasting for hierarchical data

Introduction Demand forecasting is an essential component of supply chain management. Accurate demand forecast leads to more effective production planning, better inventory management, or more accurate capacity planning. We collaborated with UXC Eclipse, a global Dynamics partner, to build a customer-tailored application for demand forecasting using Cortana Intelligence Suite components. The solution not only improved…


Set of machine learning models on Sales Pipeline

Every sales team wants to sell more. They want to know health of sales pipeline and determine whether they will meet quota at end of quarter or not. Below is comprehensive list of machine learning models you can use on sales pipeline. Good news is you need not have to spend years to built it….