Guest Blog: Using Databricks, MLflow, and Amazon SageMaker at Brandless to Bring Recommendation Systems to Production

Posted Leave a commentPosted in Company Blog, Customer Stories, Customers, Data Science and Machine Learning, Lifecycle, Machine Learning, MLflow, Operationalization, Partners, Product, Recommendation System

This is a guest blog from Adam Barnhard, Head of Data at Brandless, Inc., and Bing  Liang, Data Scientist at Brandless, Inc. Launched in July 2017, Brandless makes hundreds of high-quality items, curated for every member of your family and room of your home, and all sold at more accessible price points than similar products on the market. We […]

Announcing the MLflow 1.1 Release

Posted Leave a commentPosted in Engineering Blog, Lifecycle, Machine Learning, MLflow, Model Management, Open Source

We’re excited to announce today the release of MLflow 1.1. In this release, we’ve focused on fleshing out the tracking component of MLflow and improving visualization components in the UI. Some of the major features include: Automatic logging from TensorFlow and Keras Parallel coordinate plots in the tracking UI Pandas DataFrame based search API Java […]

Announcing the MLflow 1.0 Release

Posted Leave a commentPosted in Announcements, Company Blog, Data Science, Ecosystem, Engineering Blog, Lifecycle, Machine Learning, MLflow, Model Management, Product

MLflow is an open source platform to help manage the complete machine learning lifecycle. With MLflow, data scientists can track and share experiments locally (on a laptop) or remotely (in the cloud), package and share models across frameworks, and deploy models virtually anywhere. Today we are excited to announce the release of MLflow 1.0. Since […]