How to Use MLflow, TensorFlow, and Keras with PyCharm
At Data + AI Summit in June, we announced MLflow , an open-source platform for the complete machine learning cycle. The platform’s philosophy...
Spark + AI Summit Europe Agenda Announced
London, as a financial center and cosmopolitan city, has its historical charm, cultural draw, and technical allure for everyone, whether you are an...
A Guide to Developer, Apache Spark Use Cases, and Deep Dives Talks at Spark + AI Summit
Apache Spark is tackling new frontiers through innovations by unifying new workloads. This enables developers to combine data and AI to develop intelligent...
A Guide to AI, Machine Learning, and Data Science Talks at Spark + AI Summit
By any measurement today, in the digital media, technical conferences and citations, or searches on Google trends , the frequency of terms like...
A Guide to TensorFlow Talks at Spark + AI Summit 2018
Within a couple of years of its release as an open-source machine learning and deep learning framework, TensorFlow has seen an amazing rate...
Benchmarking Apache Spark on a Single Node Machine
Apache Spark has become the de facto unified analytics engine for big data processing in a distributed environment. Yet we are seeing more...
5 Reasons to Attend Spark + AI Summit
Spark + AI Summit will be held in San Francisco on June 4-6, 2018. Check out the full agenda and get your ticket...
Women in Big Data and Apache Spark: Bay Area Apache Spark Meetup Summary
In collaboration with the local chapter of Women in Big Data Meetup and our continuing effort by Databricks diversity team to have more...
Selected Sessions to Watch for at Spark + AI Summit 2018
Early last month, we announced our agenda for Spark + AI Summit 2018 , with over 180 selected talks with 11 tracks and...
Introducing Apache Spark 2.3
Today we are happy to announce the availability of Apache Spark 2.3.0 on Databricks as part of its Databricks Runtime 4.0. We want...