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New Methods for Improving Supply Chain Demand Forecasting

March 26, 2020 by Bryan Smith and Rob Saker in Engineering Blog
Quick link to notebooks referenced through this post. Organizations Are Rapidly Embracing Fine-Grained Demand Forecasting Retailers and Consumer Goods manufacturers are increasingly seeking...

On-Demand Webinar: Granular Demand Forecasting At Scale

February 21, 2020 by Rob Saker, Bilal Obeidat, Bryan Smith and Navin Albert in Engineering Blog
We recently hosted a live webinar — How Starbucks Forecasts Demand at Scale with Facebook Prophet and Databricks — During this webinar we...

How to Display Model Metrics in Dashboards using the MLflow Search API

February 18, 2020 by Avesh Singh, Jules Damji and Max Allen in Engineering Blog
Machine learning engineers and data scientists frequently train models to optimize a loss function. With optimization methods like gradient descent, we iteratively improve...

Automating Digital Pathology Image Analysis with Machine Learning on Databricks

January 31, 2020 by Amir Kermany and Frank Austin Nothaft in Engineering Blog
Check out our solution accelerator for automating digital pathology analysis or watch our on-demand webinar to learn more. With technological advancements in imaging...

On-Demand Webinar: Geospatial Analytics and AI in the Public Sector

January 28, 2020 by Michael Johns and Derek Yeager in Solutions
We recently hosted a live webinar — Geospatial Analytics and AI in Public Sector — during which we covered top geospatial analysis use...

Fine-Grained Time Series Forecasting At Scale With Facebook Prophet And Apache Spark

January 26, 2020 by Bilal Obeidat, Bryan Smith and Brenner Heintz in Company Blog
Try this time series forecasting notebook in our Solution Accelerator for Demand Forecasting . Advances in time series forecasting are enabling retailers to...

Solving the World’s Toughest Problems with the Growing Open Source Ecosystem and Databricks

January 23, 2020 by Reynold Xin in Platform Blog
We started Databricks in 2013 in a tiny little office in Berkeley with the belief that data has the potential to solve the...

Automate Deployment and Testing with Databricks Notebook + MLflow

January 15, 2020 by Li Yu, Jonathan Eng, Yong Sheng Huang and Peter Tamisin in Engineering Blog
Today many data science (DS) organizations are accelerating the agile analytics development process using Databricks notebooks. Fully leveraging the distributed computing power of...

Better Machine Learning through Active Learning

January 15, 2020 by Sean Owen in Company Blog
Try this notebook to reproduce the steps outlined below Machine learning models can seem like magical savants. They can distinguish hot dogs from...

Processing Geospatial Data at Scale With Databricks

December 4, 2019 by Nima Razavi and Michael Johns in Solutions
This blog was written 3 years ago. Please refer to these articles for up-to-date approaches to geospatial processing and analytics with your Databricks...
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