Databricks January 2018 Newsletter - Matei's 2018 Prediction, Forrester and Overstock webinar, eBook on ML and AI, and more.
10 Must-Haves to Deploy Machine Learning and AI in the Enterprise
Join Forrester VP & Principal Analyst, Mike Gualtieri, as he shares data on the top trends in machine learning. Guest presenters include the data science team from Overstock.com who will showcase how they leverage Databricks to create a one-to-one marketing machine.
Matei Zaharia's Predictions for 2018: Big Data and AI
Don't miss this webinar as Matei Zaharia, who started the Apache Spark project in 2009, shares his perspective on which big data and AI trends will come to fruition in 2018.
Spark + AI Summit – Call for Papers
Microsoft Webinar: Accelerate Innovation with Microsoft Azure Databricks
Join this webinar to see how to get started with Azure Databricks. The webinar will provide an overview of the product, a demonstration, and next steps to get started with Azure Databricks.
eBook: The Democratization of AI and Deep Learning
Read this eBook to learn how to use deep learning and artificial intelligence to solve real-world problems.
Video: Unifying People, Process, and Platform — The Movie
For those of you who are still new to Databricks, watch this video for a quick intro of how the Databricks Unified Analytics Platform enables data teams to come together.
Blog: Databricks and Apache Spark 2017 Year in Review
A great read that reflects on what we have as a company and community achieved collectively in 2017.
Blog: Overstock.com Marketing + Databricks = Data Science at Scale
A guest blog post from the data science team at Overstock.com showcasing how they were able to start up new machine learning models 5x faster with Databricks.
How Databricks Helps Optimize the Largest Wifi Network for Performance and Availability
Accelerate Innovation with Microsoft Azure Databricks
Apache Spark News
The Architecture of the Next CERN Accelerator Logging Service
Upcoming Apache Spark Events
Apache Spark Deep Learning Primer: TensorFlow, TensorFrames, and Keras
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