A Guide to Data + AI Summit Sessions: Machine Learning, Data Engineering, Apache Spark and More
We are only a few weeks away from Data + AI Summit, returning May 24–28. If you haven’t signed up yet, take advantage of free registration for five days of virtual engagement: training, talks, meetups, AMAs and community camaraderie. To help you navigate through hundreds of sessions, I am sharing some of the content —...
7 Reasons to Learn PyTorch on Databricks
What expedites the process of learning new concepts, languages or systems? When learning a new task, do you look for analogs from skills you already possess? Across all learning endeavors, three favorable characteristics stand out: familiarity, clarity and simplicity. Familiarity eases the transition because of a recognizable link between the old and new ways of...
MLflow Model Registry on Databricks Simplifies MLOps With CI/CD Features
MLflow helps organizations manage the ML lifecycle through the ability to track experiment metrics, parameters, and artifacts, as well as deploy models to batch or real-time serving systems. The MLflow Model Registry provides a central repository to manage the model deployment lifecycle, acting as the hub between experimentation and deployment. A critical part of MLOps,...
MLflow 1.12 Features Extended PyTorch Integration
MLflow 1.12 features include extended PyTorch integration, SHAP model explainability, autologging MLflow entities for supported model flavors, and a number of UI and document improvements. Now available on PyPI and the docs online, you can install this new release with pip install mlflow==1.12.0 as described in the MLflow quickstart guide. In this blog, we briefly...
A Guide to MLflow Talks at Data + AI Summit Europe 2020
In the last two years since its release, MLflow has seen a rapid adoption among enterprises and the data science community. With over 2M downloads, 260 contributors, and 100+ organizations contributing, the momentum seems to grow each year. We have put together a short list of picks–keynotes, tutorials, and sessions–for MLflow: how the community and...
Ten Simple Databricks Notebook Tips & Tricks for Data Scientists
Often, small things make a huge difference, hence the adage that "some of the best ideas are simple!" Over the course of a few releases this year, and in our efforts to make Databricks simple, we have added several small features in our notebooks that make a huge difference. In this blog and the accompanying...
Data + AI Summit Europe Goes Virtual With a Data-Centric Agenda
Technical conferences evolve over time. They expand beyond their initial focus, adding new technologies, attracting new attendees and broadening their range of sessions and speakers. Formerly known as Spark + AI Summit Europe, the new Data + AI Summit Europe has embraced a data-centric approach — focusing on Apache Spark, MLflow and Delta Lake use...
Spark + AI Summit Reflections
Developers attending a conference have high expectations: what knowledge gaps they’ll fill; what innovative ideas or inspirational thoughts they’ll take away; who to contact for technical questions, during and after the conference; what technical trends are emerging in their domain of expertise; what serendipitous connections they’ll make and foster; and what theme will resonate across...
Databricks Extends MLflow Model Registry with Enterprise Features
We are excited to announce new enterprise grade features for the MLflow Model Registry on Databricks. The Model Registry is now enabled by default for all customers using Databricks' Unified Analytics Platform. In this blog, we want to highlight the benefits of the Model Registry as a centralized hub for model management, how data teams...
Spark + AI Summit Is Going Virtual with an Expanded Agenda
Over the years, technical conferences tend to expand beyond their initial focus, adding new technologies, types of attendees, and a broader range of sessions and speakers. From its original focus on Apache Spark™, the Spark + AI Summit has extended its scope to include not only data engineering and infrastructure, but also machine learning automation...
