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Data Engineering Meet-up with Matei Zaharia | Berlin

Community Event

Berlin, DE

For our 7th installment of the series we have a special guest in Matei Zaharia. Matei is an Assistant Professor of Computer Science at Stanford University and Chief Technologist at Databricks. He started the Apache Spark project during his PhD at UC Berkeley in 2009. Today, Matei tech-leads the MLflow development effort at Databricks. Register Now!

AWS + Databricks Dev Day | Dallas

Regional Event

Dallas, TX

Join this half-day workshop to learn how unified analytics can bring data science and engineering together to accelerate your ML efforts. In this workshop, we’ll cover best practices for enterprises to use powerful open source technologies to simplify and scale your ML efforts. We’ll discuss how to leverage Apache Spark™, the de-facto data processing and analytics engine in enterprises today, for data preparation as it unifies data at massive scale across various sources.

Unified Analytics | Workshop w/ Microsoft | Salt Lake City

Regional Event

Salt Lake City, UT

Join this half-day workshop to learn how unified analytics can bring data science and engineering together to accelerate your ML efforts. In this workshop, we’ll cover best practices for enterprises to use powerful open source technologies to simplify and scale your ML efforts. We’ll discuss how to leverage Apache Spark™, the de-facto data processing and analytics engine in enterprises today, for data preparation as it unifies data at massive scale across various sources.

Deep Learning Fundamental Series: Applying your Convolutional Neural Network

Webinar

Learn how convolutions works, discuss some of the ImageNet architectures and see how to apply a convolutional neural network using the ImageNet scenario.

Unified Analytics – Unifying Data Pipelines & Machine Learning with Apache Spark [Conducted in Japanese]

Regional Event

Tokyo, Japan

In this workshop, we’ll cover best practices for enterprises to use powerful open source technologies to simplify and scale your ML efforts. We’ll discuss how to leverage Apache Spark™, the de-facto data processing and analytics engine in enterprises today, for data preparation as it unifies data at massive scale across various sources. You’ll learn how to use ML frameworks (i.e. Tensorflow, XGBoost, Scikit-Learn, etc.) to train models based on different requirements. And finally, you can learn how to use MLflow to track experiment runs between multiple users within a reproducible environment, and manage the deployment of models to production.

Unified Analytics | Workshop w/ Microsoft | Montreal

Regional Event

Montreal, Canada

Join this half-day workshop to learn how unified analytics can bring data science and engineering together to accelerate your ML efforts. In this workshop, we’ll cover best practices for enterprises to use powerful open source technologies to simplify and scale your ML efforts. We’ll discuss how to leverage Apache Spark™, the de-facto data processing and analytics engine in enterprises today, for data preparation as it unifies data at massive scale across various sources.

Unified Analytics | Workshop w/ Microsoft | Philadelphia

Regional Event

Malvern, PA

Join this half-day workshop to learn how unified analytics can bring data science and engineering together to accelerate your ML efforts. In this workshop, we’ll cover best practices for enterprises to use powerful open source technologies to simplify and scale your ML efforts. We’ll discuss how to leverage Apache Spark™, the de-facto data processing and analytics engine in enterprises today, for data preparation as it unifies data at massive scale across various sources.

Unifying Data Pipelines and Machine Learning with Apache Spark™

Regional Event

Montreal, Canada

Every enterprise today wants to accelerate innovation by building AI into their business. However, most companies struggle with preparing large datasets for analytics, managing the proliferation of ML frameworks, and moving models in development to production.

LoyaltyOne Simplifies and Scales Data & Analytics Pipelines with Delta Lake

Webinar

Learn how LoyaltyOne—a loyalty marketing services provider—used open-source Delta Lake on Databricks and Amazon Web Services (AWS) to create automated data pipelines that feed thousands of ML and analytics models, accelerating and enhancing customer churn and recommendation engines. LoyaltyOne is also scaling their analytics by using AutoML on Databricks, accommodating developers with a range of experience.

Simplifying Production Machine Learning with MLflow

Community Event

Toronto, ON

Building and deploying a machine learning model can be difficult to do once. Enabling other engineers (or yourself, one month later) to reproduce your pipeline, to compare the results of different versions, to track what’s running where, and to redeploy and rollback updated models is much harder. In this talk, Matei Zaharia, the Co-founder and Chief Technologist from Databricks, will introduce MLflow, a new open-source project launched by Databricks that simplifies the machine learning lifecycle.